Judicial virtues and decision-making in the VCAT Guardianship List.

PubMed

Polkinghorn, Richard

2014-06-01

The contemporary legal theory of virtue jurisprudence provides great insight into the proper practice of Australian tribunal members and the desired operation of tribunals. Virtue jurisprudence identifies the attributes of "good" tribunal members and provides guidance on how legal disputes should be decided. This article focuses on the fundamental virtues relevant to tribunal practice in the Guardianship List of the Victorian Civil and Administrative Tribunal. The special features of this tribunal jurisdiction, particularly the disadvantaged nature of its primary client group, require tribunal members to undertake a fact-finding, inquisitorial role, as well as a support and advisory role. Decision-makers must also become conversant with expert evidence and the process of testing expert evidence; they cannot simply defer to the expert on issues of decision-making capacity. This analysis considers the fundamental breaches of human rights that occur when tribunal members fail to execute this multilevel task properly.

Intelligent systems for human resources.

PubMed

Kline, K B

1988-11-01

An intelligent system contains knowledge about some domain; it has sophisticated decision-making processes and the ability to explain its actions. The most important aspect of an intelligent system is its ability to effectively interact with humans to teach or assist complex information processing. Two intelligent systems are Intelligent Tutoring Systems (ITs) and Expert Systems. The ITSs provide instruction to a student similar to a human tutor. The ITSs capture individual performance and tutor deficiencies. These systems consist of an expert module, which contains the knowledge or material to be taught; the student module, which contains a representation of the knowledge the student knows and does not know about the domain; and the instructional or teaching module, which selects specific knowledge to teach, the instructional strategy, and provides assistance to the student to tutor deficiencies. Expert systems contain an expert's knowledge about some domain and perform specialized tasks or aid a novice in the performance of certain tasks. The most important part of an expert system is the knowledge base. This knowledge base contains all the specialized and technical knowledge an expert possesses. For an expert system to interact effectively with humans, it must have the ability to explain its actions. Use of intelligent systems can have a profound effect on human resources. The ITSs can provide better training by tutoring on an individual basis, and the expert systems can make better use of human resources through job aiding and performing complex tasks. With increasing training requirements and "doing more with less," intelligent systems can have a positive effect on human resources.

Organizational decision to adopt hospital information system: an empirical investigation in the case of Malaysian public hospitals.

PubMed

Ahmadi, Hossein; Nilashi, Mehrbakhsh; Ibrahim, Othman

2015-03-01

This study mainly integrates the mature Technology-Organization-Environment (TOE) framework and recently developed Human-Organization-Technology (HOT) fit model to identify factors that affect the hospital decision in adopting Hospital Information System (HIS). Accordingly, a hybrid Multi-Criteria-Decision-Making (MCDM) model is used to address the dependence relationships of factors with the aid of Analytic Network Processes (ANP) and Decision Making Trial and Evaluation Laboratory (DEMATEL) approaches. The initial model of the study is designed by considering four main dimensions with 13 variables as organizational innovation adoption factors with respect to HIS. By using DEMATEL, the interdependencies strength among the dimensions and variables are tested. The ANP method is then adopted in order to determine the relative importance of the adoption factors, and is used to identify how these factors are weighted and prioritized by the public hospital professionals, who are wholly familiar with the HIS and have years of experience in decision making in hospitals' Information System (IS) department. The results of this study indicate that from the experts' viewpoint "Perceived Technical Competence" is the most important factor in the Human dimension. In the Technology dimension, the experts agree that the "Relative Advantage" is more important in relation to the other factors. In the Organization dimension, "Hospital Size" is considered more important rather than others. And, in the Environment dimension, according to the experts judgment, "Government Policy" is the most important factor. The results of ANP survey from experts also reveal that the experts in the HIS field believed that these factors should not be overlooked by managers of hospitals and the adoption of HIS is more related to more consideration of these factors. In addition, from the results, it is found that the experts are more concerned about Environment and Technology for the adoption HIS. The findings of this study make a novel contribution in the context of healthcare industry that is to improve the decision process of innovation in adoption stage and to help enhance more the diffusion of IS in the hospital setting, which by doing so, can provide plenty of profits to the patient community and the hospitals. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Introduction to cognitive processes of expert pilots.

PubMed

Adams, R J; Ericsson, A E

2000-10-01

This report addresses the historical problem that a very high percentage of accidents have been classified as involving "pilot error." Through extensive research since 1977, the Federal Aviation Administration determined that the predominant underlying cause of these types of accidents involved decisional problems or cognitive information processing. To attack these problems, Aeronautical Decision Making (ADM) training materials were developed and tested for ten years. Since the publication of the ADM training manuals in 1987, significant reductions in human performance error (HPE) accidents have been documented both in the U.S. and world wide. However, shortcomings have been observed in the use of these materials for recurrency training and in their relevance to more experienced pilots. The following discussion defines the differences between expert and novice decision makers from a cognitive information processing perspective, correlates the development of expert pilot cognitive processes with training and experience, and reviews accident scenarios which exemplify those processes. This introductory material is a necessary prerequisite to an understanding of how to formulate expert pilot decision making training innovations; and, to continue the record of improved safety through ADM training.

Comparison of Cramer classification between Toxtree, the OECD QSAR Toolbox and expert judgment.

PubMed

Bhatia, Sneha; Schultz, Terry; Roberts, David; Shen, Jie; Kromidas, Lambros; Marie Api, Anne

2015-02-01

The Threshold of Toxicological Concern (TTC) is a pragmatic approach in risk assessment. In the absence of data, it sets up levels of human exposure that are considered to have no appreciable risk to human health. The Cramer decision tree is used extensively to determine these exposure thresholds by categorizing non-carcinogenic chemicals into three different structural classes. Therefore, assigning an accurate Cramer class to a material is a crucial step to preserve the integrity of the risk assessment. In this study the Cramer class of over 1000 fragrance materials across diverse chemical classes were determined by using Toxtree (TT), the OECD QSAR Toolbox (TB), and expert judgment. Disconcordance was observed between TT and the TB. A total of 165 materials (16%) showed different results from the two programs. The overall concordance for Cramer classification between TT and expert judgment is 83%, while the concordance between the TB and expert judgment is 77%. Amines, lactones and heterocycles have the lowest percent agreement with expert judgment for TT and the TB. For amines, the expert judgment agreement is 45% for TT and 55% for the TB. For heterocycles, the expert judgment agreement is 55% for TT and the TB. For lactones, the expert judgment agreement is 56% for TT and 50% for the TB. Additional analyses were conducted to determine the concordance within various chemical classes. Critical checkpoints in the decision tree are identified. Strategies and guidance on determining the Cramer class for various chemical classes are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Expert Systems: A Conceptual Analysis and Prospects for Their Library Applications.

ERIC Educational Resources Information Center

Dubey, Yogendra P.

This paper begins with a discussion of the decision-making process. The application of operations research technologies to managerial decision-making is noted, and the development of management information systems in organizations and some limitations of these systems are discussed. An overview of the Human Information Processing System (HIPS)…

Nickel cadmium battery expert system

NASA Technical Reports Server (NTRS)

1986-01-01

The applicability of artificial intelligence methodologies for the automation of energy storage management, in this case, nickel cadmium batteries, is demonstrated. With the Hubble Space Telescope Electrical Power System (HST/EPS) testbed as the application domain, an expert system was developed which incorporates the physical characterization of the EPS, in particular, the nickel cadmium batteries, as well as the human's operational knowledge. The expert system returns not only fault diagnostics but also status and advice along with justifications and explanations in the form of decision support.

Application of expert systems in project management decision aiding

NASA Technical Reports Server (NTRS)

Harris, Regina; Shaffer, Steven; Stokes, James; Goldstein, David

1987-01-01

The feasibility of developing an expert systems-based project management decision aid to enhance the performance of NASA project managers was assessed. The research effort included extensive literature reviews in the areas of project management, project management decision aiding, expert systems technology, and human-computer interface engineering. Literature reviews were augmented by focused interviews with NASA managers. Time estimation for project scheduling was identified as the target activity for decision augmentation, and a design was developed for an Integrated NASA System for Intelligent Time Estimation (INSITE). The proposed INSITE design was judged feasible with a low level of risk. A partial proof-of-concept experiment was performed and was successful. Specific conclusions drawn from the research and analyses are included. The INSITE concept is potentially applicable in any management sphere, commercial or government, where time estimation is required for project scheduling. As project scheduling is a nearly universal management activity, the range of possibilities is considerable. The INSITE concept also holds potential for enhancing other management tasks, especially in areas such as cost estimation, where estimation-by-analogy is already a proven method.

Grey situation group decision-making method based on prospect theory.

PubMed

Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

2014-01-01

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.

Grey Situation Group Decision-Making Method Based on Prospect Theory

PubMed Central

Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

2014-01-01

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example. PMID:25197706

Characterization of Decision Making Behaviors Associated with Human Systems Integration (HSI) Design Tradeoffs: Subject Matter Expert Interviews

DTIC Science & Technology

2014-11-18

this research was to characterize the naturalistic decision making process used in Naval Aviation acquisition to assess cost, schedule and...Naval Aviation acquisitions can be identified, which can support the future development of new processes and tools for training and decision making...part of Department of Defense acquisition processes , HSI ensures that operator, maintainer and sustainer considerations are incorporated into

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

PubMed

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

Four Common Simplifications of Multi-Criteria Decision Analysis do not hold for River Rehabilitation

PubMed Central

2016-01-01

River rehabilitation aims at alleviating negative effects of human impacts such as loss of biodiversity and reduction of ecosystem services. Such interventions entail difficult trade-offs between different ecological and often socio-economic objectives. Multi-Criteria Decision Analysis (MCDA) is a very suitable approach that helps assessing the current ecological state and prioritizing river rehabilitation measures in a standardized way, based on stakeholder or expert preferences. Applications of MCDA in river rehabilitation projects are often simplified, i.e. using a limited number of objectives and indicators, assuming linear value functions, aggregating individual indicator assessments additively, and/or assuming risk neutrality of experts. Here, we demonstrate an implementation of MCDA expert preference assessments to river rehabilitation and provide ample material for other applications. To test whether the above simplifications reflect common expert opinion, we carried out very detailed interviews with five river ecologists and a hydraulic engineer. We defined essential objectives and measurable quality indicators (attributes), elicited the experts´ preferences for objectives on a standardized scale (value functions) and their risk attitude, and identified suitable aggregation methods. The experts recommended an extensive objectives hierarchy including between 54 and 93 essential objectives and between 37 to 61 essential attributes. For 81% of these, they defined non-linear value functions and in 76% recommended multiplicative aggregation. The experts were risk averse or risk prone (but never risk neutral), depending on the current ecological state of the river, and the experts´ personal importance of objectives. We conclude that the four commonly applied simplifications clearly do not reflect the opinion of river rehabilitation experts. The optimal level of model complexity, however, remains highly case-study specific depending on data and resource availability, the context, and the complexity of the decision problem. PMID:26954353

Getting Mental Models and Computer Models to Cooperate

NASA Technical Reports Server (NTRS)

Sheridan, T. B.; Roseborough, J.; Charney, L.; Mendel, M.

1984-01-01

A qualitative theory of supervisory control is outlined wherein the mental models of one or more human operators are related to the knowledge representations within automatic controllers (observers, estimators) and operator decision aids (expert systems, advice-givers). Methods of quantifying knowledge and the calibration of one knowledge representation to another (human, computer, or objective truth) are discussed. Ongoing experiments in the use of decision aids for exploring one's own objective function or exploring system constraints and control strategies are described.

Multi-criteria decision analysis tools for prioritising emerging or re-emerging infectious diseases associated with climate change in Canada.

PubMed

Cox, Ruth; Sanchez, Javier; Revie, Crawford W

2013-01-01

Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software 'M-MACBETH'. The tools were trialed on nine 'test' pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued.

Multi-Criteria Decision Analysis Tools for Prioritising Emerging or Re-Emerging Infectious Diseases Associated with Climate Change in Canada

PubMed Central

Cox, Ruth; Sanchez, Javier; Revie, Crawford W.

2013-01-01

Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software ‘M-MACBETH’. The tools were trialed on nine ‘test’ pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued. PMID:23950868

A simple system for detection of EEG artifacts in polysomnographic recordings.

PubMed

Durka, P J; Klekowicz, H; Blinowska, K J; Szelenberger, W; Niemcewicz, Sz

2003-04-01

We present an efficient parametric system for automatic detection of electroencephalogram (EEG) artifacts in polysomnographic recordings. For each of the selected types of artifacts, a relevant parameter was calculated for a given epoch. If any of these parameters exceeded a threshold, the epoch was marked as an artifact. Performance of the system, evaluated on 18 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the interexpert agreement and the repeatability of expert's decisions, assessed via a double-blind test. Complete software (Matlab source code) for the presented system is freely available from the Internet at http://brain.fuw.edu.pl/artifacts.

A Cognitive Architecture for Human Performance Process Model Research

DTIC Science & Technology

1992-11-01

individually defined, updatable world representation which is a description of the world as the operator knows it. It contains rules for decisions, an...operate it), and rules of engagement (knowledge about the operator’s expected behavior). The HPP model works in the following way. Information enters...based models depict the problem-solving processes of experts. The experts’ knowledge is represented in symbol structures, along with rules for

a Novel Approach to Support Majority Voting in Spatial Group Mcdm Using Density Induced Owa Operator for Seismic Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Moradi, M.; Delavar, M. R.; Moshiri, B.; Khamespanah, F.

2014-10-01

Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other's opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts' opinions.

Web Spam, Social Propaganda and the Evolution of Search Engine Rankings

NASA Astrophysics Data System (ADS)

Metaxas, Panagiotis Takis

Search Engines have greatly influenced the way we experience the web. Since the early days of the web, users have been relying on them to get informed and make decisions. When the web was relatively small, web directories were built and maintained using human experts to screen and categorize pages according to their characteristics. By the mid 1990's, however, it was apparent that the human expert model of categorizing web pages does not scale. The first search engines appeared and they have been evolving ever since, taking over the role that web directories used to play.

Support vector machines

NASA Technical Reports Server (NTRS)

Garay, Michael J.; Mazzoni, Dominic; Davies, Roger; Wagstaff, Kiri

2004-01-01

Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.

The aggregate complexity of decisions in the game of Go

NASA Astrophysics Data System (ADS)

Harré, M. S.; Bossomaier, T.; Gillett, A.; Snyder, A.

2011-04-01

Artificial intelligence (AI) research is fast approaching, or perhaps has already reached, a bottleneck whereby further advancement towards practical human-like reasoning in complex tasks needs further quantified input from large studies of human decision-making. Previous studies in psychology, for example, often rely on relatively small cohorts and very specific tasks. These studies have strongly influenced some of the core notions in AI research such as the reinforcement learning and the exploration versus exploitation paradigms. With the goal of contributing to this direction in AI developments we present our findings on the evolution towards world-class decision-making across large cohorts of subjects in the formidable game of Go. Some of these findings directly support previous work on how experts develop their skills but we also report on several previously unknown aspects of the development of expertise that suggests new avenues for AI research to explore. In particular, at the level of play that has so far eluded current AI systems for Go, we are able to quantify the lack of `predictability' of experts and how this changes with their level of skill.

Utilization of a cognitive task analysis for laparoscopic appendectomy to identify differentiated intraoperative teaching objectives.

PubMed

Smink, Douglas S; Peyre, Sarah E; Soybel, David I; Tavakkolizadeh, Ali; Vernon, Ashley H; Anastakis, Dimitri J

2012-04-01

Experts become automated when performing surgery, making it difficult to teach complex procedures to trainees. Cognitive task analysis (CTA) enables experts to articulate operative steps and cognitive decisions in complex procedures such as laparoscopic appendectomy, which can then be used to identify central teaching points. Three local surgeon experts in laparoscopic appendectomy were interviewed using critical decision method-based CTA methodology. Interview transcripts were analyzed, and a cognitive demands table (CDT) was created for each expert. The individual CDTs were reviewed by each expert for completeness and then combined into a master CDT. Percentage agreement on operative steps and decision points was calculated for each expert. The experts then participated in a consensus meeting to review the master CDT. Each surgeon expert was asked to identify in the master CDT the most important teaching objectives for junior-level and senior-level residents. The experts' responses for junior-level and senior-level residents were compared using a χ(2) test. The surgeon experts identified 24 operative steps and 27 decision points. Eighteen of the 24 operative steps (75%) were identified by all 3 surgeon experts. The percentage of operative steps identified was high for each surgeon expert (96% for surgeon 1, 79% for surgeon 2, and 83% for surgeon 3). Of the 27 decision points, only 5 (19%) were identified by all 3 surgeon experts. The percentage of decision points identified varied by surgeon expert (78% for surgeon 1, 59% for surgeon 2, and 48% for surgeon 3). When asked to identify key teaching points, the surgeon experts were more likely to identify operative steps for junior residents (9 operative steps and 6 decision points) and decision points for senior residents (4 operative steps and 13 decision points) (P < .01). CTA can deconstruct the essential operative steps and decision points associated with performing a laparoscopic appendectomy. These results provide a framework to identify key teaching principles to guide intraoperative instruction. These learning objectives could be used to guide resident level-appropriate teaching of an essential general surgery procedure. Copyright © 2012 Elsevier Inc. All rights reserved.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

Expert system training and control based on the fuzzy relation matrix

NASA Technical Reports Server (NTRS)

Ren, Jie; Sheridan, T. B.

1991-01-01

Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model.

Distributed Web-Based Expert System for Launch Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge E.; Thirumalainambi, Rajkumar

2005-01-01

The simulation and modeling of launch operations is based on a representation of the organization of the operations suitable to experiment of the physical, procedural, software, hardware and psychological aspects of space flight operations. The virtual test bed consists of a weather expert system to advice on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, and the risk impact on human health. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.

CLIPS: The C language integrated production system

NASA Technical Reports Server (NTRS)

Riley, Gary

1994-01-01

Expert systems are computer programs which emulate human expertise in well defined problem domains. The potential payoff from expert systems is high: valuable expertise can be captured and preserved, repetitive and/or mundane tasks requiring human expertise can be automated, and uniformity can be applied in decision making processes. The C Language Integrated Production System (CLIPS) is an expert system building tool, developed at the Johnson Space Center, which provides a complete environment for the development and delivery of rule and/or object based expert systems. CLIPS was specifically designed to provide a low cost option for developing and deploying expert system applications across a wide range of hardware platforms. The commercial potential of CLIPS is vast. Currently, CLIPS is being used by over 5,000 individuals throughout the public and private sector. Because the CLIPS source code is readily available, numerous groups have used CLIPS as the basis for their own expert system tools. To date, three commercially available tools have been derived from CLIPS. In general, the development of CLIPS has helped to improve the ability to deliver expert system technology throughout the public and private sectors for a wide range of applications and diverse computing environments.

Assessing ethical problem solving by reasoning rather than decision making.

PubMed

Tsai, Tsuen-Chiuan; Harasym, Peter H; Coderre, Sylvain; McLaughlin, Kevin; Donnon, Tyrone

2009-12-01

The assessment of ethical problem solving in medicine has been controversial and challenging. The purposes of this study were: (i) to create a new instrument to measure doctors' decisions on and reasoning approach towards resolving ethical problems; (ii) to evaluate the scores generated by the new instrument for their reliability and validity, and (iii) to compare doctors' ethical reasoning abilities between countries and among medical students, residents and experts. This study used 15 clinical vignettes and the think-aloud method to identify the processes and components involved in ethical problem solving. Subjects included volunteer ethics experts, postgraduate Year 2 residents and pre-clerkship medical students. The interview data were coded using the instruments of the decision score and Ethical Reasoning Inventory (ERI). The ERI assessed the quality of ethical reasoning for a particular case (Part I) and for an individual globally across all the vignettes (Part II). There were 17 Canadian and 32 Taiwanese subjects. Based on the Canadian standard, the decision scores between Taiwanese and Canadian subjects differed significantly, but made no discrimination among the three levels of expertise. Scores on the ERI Parts I and II, which reflect doctors' reasoning quality, differed between countries and among different levels of expertise in Taiwan, providing evidence of construct validity. In addition, experts had a greater organised knowledge structure and considered more relevant variables in the process of arriving at ethical decisions than did residents or students. The reliability of ERI scores was 0.70-0.99 on Part I and 0.75-0.80 on Part II. Expertise in solving ethical problems could not be differentiated by the decisions made, but could be differentiated according to the reasoning used to make those decisions. The difference between Taiwanese and Canadian experts suggests that cultural considerations come into play in the decisions that are made in the course of providing humane care to patients.

Human-Computer Interaction with Medical Decisions Support Systems

NASA Technical Reports Server (NTRS)

Adolf, Jurine A.; Holden, Kritina L.

1994-01-01

Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

Delegating Decisions to Experts

ERIC Educational Resources Information Center

Li, Hao; Suen, Wing

2004-01-01

We present a model of delegation with self-interested and privately informed experts. A team of experts with extreme but opposite biases is acceptable to a wide range of decision makers with diverse preferences, but the value of expertise from such a team is low. A decision maker wants to appoint experts who are less partisan than he is in order…

Acquisition and production of skilled behavior in dynamic decision-making tasks

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1992-01-01

Currently, two main approaches exist for improving the human-machine interface component of a system in order to improve overall system performance - display enhancement and intelligent decision making. Discussed here are the characteristic issues of these two decision-making strategies. Differences in expert and novice decision making are described in order to help determine whether a particular strategy may be better for a particular type of user. Research is outlined to compare and contrast the two technologies, as well as to examine the interaction effects introduced by the different skill levels and the different methods for training operators.

Distributed medical image analysis and diagnosis through crowd-sourced games: a malaria case study.

PubMed

Mavandadi, Sam; Dimitrov, Stoyan; Feng, Steve; Yu, Frank; Sikora, Uzair; Yaglidere, Oguzhan; Padmanabhan, Swati; Nielsen, Karin; Ozcan, Aydogan

2012-01-01

In this work we investigate whether the innate visual recognition and learning capabilities of untrained humans can be used in conducting reliable microscopic analysis of biomedical samples toward diagnosis. For this purpose, we designed entertaining digital games that are interfaced with artificial learning and processing back-ends to demonstrate that in the case of binary medical diagnostics decisions (e.g., infected vs. uninfected), with the use of crowd-sourced games it is possible to approach the accuracy of medical experts in making such diagnoses. Specifically, using non-expert gamers we report diagnosis of malaria infected red blood cells with an accuracy that is within 1.25% of the diagnostics decisions made by a trained medical professional.

Application Of The CSRL Language To The Design Of Diagnostic Expert Systems: The Moodis Experience, A Preliminary Report

NASA Astrophysics Data System (ADS)

Bravos, Angelo; Hill, Howard; Choca, James; Bresolin, Linda B.; Bresolin, Michael J.

1986-03-01

Computer technology is rapidly becoming an inseparable part of many health science specialties. Recently, a new area of computer technology, namely Artificial Intelligence, has been applied toward assisting the medical experts in their diagnostic and therapeutic decision making process. MOODIS is an experimental diagnostic expert system which assists Psychiatry specialists in diagnosing human Mood Disorders, better known as Affective Disorders. Its diagnostic methodology is patterned after MDX, a diagnostic expert system developed at LAIR (Laboratory for Artificial Intelligence Research) of Ohio State University. MOODIS is implemented in CSRL (Conceptual Structures Representation Language) also developed at LAIR. This paper describes MOODIS in terms of conceptualization and requirements, and discusses why the MDX approach and CSRL were chosen.

Proceedings of the 1986 IEEE international conference on systems, man and cybernetics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1986-01-01

This book presents the papers given at a conference on man-machine systems. Topics considered at the conference included neural model-based cognitive theory and engineering, user interfaces, adaptive and learning systems, human interaction with robotics, decision making, the testing and evaluation of expert systems, software development, international conflict resolution, intelligent interfaces, automation in man-machine system design aiding, knowledge acquisition in expert systems, advanced architectures for artificial intelligence, pattern recognition, knowledge bases, and machine vision.

Human Factors in Automated and Robotic Space Systems: Proceedings of a symposium. Part 1

NASA Technical Reports Server (NTRS)

Sheridan, Thomas B. (Editor); Kruser, Dana S. (Editor); Deutsch, Stanley (Editor)

1987-01-01

Human factors research likely to produce results applicable to the development of a NASA space station is discussed. The particular sessions covered in Part 1 include: (1) system productivity -- people and machines; (2) expert systems and their use; (3) language and displays for human-computer communication; and (4) computer aided monitoring and decision making. Papers from each subject area are reproduced and the discussions from each area are summarized.

Crossword expertise as recognitional decision making: an artificial intelligence approach

PubMed Central

Thanasuan, Kejkaew; Mueller, Shane T.

2014-01-01

The skills required to solve crossword puzzles involve two important aspects of lexical memory: semantic information in the form of clues that indicate the meaning of the answer, and orthographic patterns that constrain the possibilities but may also provide hints to possible answers. Mueller and Thanasuan (2013) proposed a model accounting for the simple memory access processes involved in solving individual crossword clues, but expert solvers also bring additional skills and strategies to bear on solving complete puzzles. In this paper, we developed an computational model of crossword solving that incorporates strategic and other factors, and is capable of solving crossword puzzles in a human-like fashion, in order to understand the complete set of skills needed to solve a crossword puzzle. We compare our models to human expert and novice solvers to investigate how different strategic and structural factors in crossword play impact overall performance. Results reveal that expert crossword solving relies heavily on fluent semantic memory search and retrieval, which appear to allow experts to take better advantage of orthographic-route solutions, and experts employ strategies that enable them to use orthographic information. Furthermore, other processes central to traditional AI models (error correction and backtracking) appear to be of less importance for human players. PMID:25309483

Crossword expertise as recognitional decision making: an artificial intelligence approach.

PubMed

Thanasuan, Kejkaew; Mueller, Shane T

2014-01-01

THE SKILLS REQUIRED TO SOLVE CROSSWORD PUZZLES INVOLVE TWO IMPORTANT ASPECTS OF LEXICAL MEMORY: semantic information in the form of clues that indicate the meaning of the answer, and orthographic patterns that constrain the possibilities but may also provide hints to possible answers. Mueller and Thanasuan (2013) proposed a model accounting for the simple memory access processes involved in solving individual crossword clues, but expert solvers also bring additional skills and strategies to bear on solving complete puzzles. In this paper, we developed an computational model of crossword solving that incorporates strategic and other factors, and is capable of solving crossword puzzles in a human-like fashion, in order to understand the complete set of skills needed to solve a crossword puzzle. We compare our models to human expert and novice solvers to investigate how different strategic and structural factors in crossword play impact overall performance. Results reveal that expert crossword solving relies heavily on fluent semantic memory search and retrieval, which appear to allow experts to take better advantage of orthographic-route solutions, and experts employ strategies that enable them to use orthographic information. Furthermore, other processes central to traditional AI models (error correction and backtracking) appear to be of less importance for human players.

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

PubMed

Fan, Bi; Li, Han-Xiong; Hu, Yong

2016-02-01

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

Workshop on Aeronautical Decision Making (ADM). Volume 1. Executive Summary

DTIC Science & Technology

1992-08-01

expert and novice pilots when a real decision was required. Aeronautical Decision Making (ADM), Crew Resource Management (CRM), Advanced Qualification Program (AQP), Cognitive Task Analysis (CTA), Expert Decision Making (EDM)

How Expert Pilots Think Cognitive Processes in Expert Decision Making

DTIC Science & Technology

1993-02-01

Management (CRM) This document is available to the public Advanced Qualification Program (AQP) through the National Technical Information Cognitive Task Analysis (CTA...8217 Selecting realistic EDM scenarios with critical events and performing a cognitive task analysis of novice vs. expert decision making for these events...scenarios with critical events and performing a cognitive task analysis of novice vs. expert decision making for these events is a basic requirement for

Complacency and bias in human use of automation: an attentional integration.

PubMed

Parasuraman, Raja; Manzey, Dietrich H

2010-06-01

Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Automation-related complacency and automation bias have typically been considered separately and independently. Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator's attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.

Empirically derived guidance for social scientists to influence environmental policy

PubMed Central

Brown, Katrina; Crissman, Charles; De Young, Cassandra; Gooch, Margaret; James, Craig; Jessen, Sabine; Johnson, Dave; Marshall, Paul; Wachenfeld, Dave; Wrigley, Damian

2017-01-01

Failure to stem trends of ecological disruption and associated loss of ecosystem services worldwide is partly due to the inadequate integration of the human dimension into environmental decision-making. Decision-makers need knowledge of the human dimension of resource systems and of the social consequences of decision-making if environmental management is to be effective and adaptive. Social scientists have a central role to play, but little guidance exists to help them influence decision-making processes. We distil 348 years of cumulative experience shared by 31 environmental experts across three continents into advice for social scientists seeking to increase their influence in the environmental policy arena. Results focus on the importance of process, engagement, empathy and acumen and reveal the importance of understanding and actively participating in policy processes through co-producing knowledge and building trust. The insights gained during this research might empower a science-driven cultural change in science-policy relations for the routine integration of the human dimension in environmental decision making; ultimately for an improved outlook for earth’s ecosystems and the billions of people that depend on them. PMID:28278238

Designing Real-time Decision Support for Trauma Resuscitations

PubMed Central

Yadav, Kabir; Chamberlain, James M.; Lewis, Vicki R.; Abts, Natalie; Chawla, Shawn; Hernandez, Angie; Johnson, Justin; Tuveson, Genevieve; Burd, Randall S.

2016-01-01

Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed. Results Among 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert–video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low. Conclusions An eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians. PMID:26300010

Comparing the performance of expert user heuristics and an integer linear program in aircraft carrier deck operations.

PubMed

Ryan, Jason C; Banerjee, Ashis Gopal; Cummings, Mary L; Roy, Nicholas

2014-06-01

Planning operations across a number of domains can be considered as resource allocation problems with timing constraints. An unexplored instance of such a problem domain is the aircraft carrier flight deck, where, in current operations, replanning is done without the aid of any computerized decision support. Rather, veteran operators employ a set of experience-based heuristics to quickly generate new operating schedules. These expert user heuristics are neither codified nor evaluated by the United States Navy; they have grown solely from the convergent experiences of supervisory staff. As unmanned aerial vehicles (UAVs) are introduced in the aircraft carrier domain, these heuristics may require alterations due to differing capabilities. The inclusion of UAVs also allows for new opportunities for on-line planning and control, providing an alternative to the current heuristic-based replanning methodology. To investigate these issues formally, we have developed a decision support system for flight deck operations that utilizes a conventional integer linear program-based planning algorithm. In this system, a human operator sets both the goals and constraints for the algorithm, which then returns a proposed schedule for operator approval. As a part of validating this system, the performance of this collaborative human-automation planner was compared with that of the expert user heuristics over a set of test scenarios. The resulting analysis shows that human heuristics often outperform the plans produced by an optimization algorithm, but are also often more conservative.

Evaluating sustainable energy harvesting systems for human implantable sensors

NASA Astrophysics Data System (ADS)

AL-Oqla, Faris M.; Omar, Amjad A.; Fares, Osama

2018-03-01

Achieving most appropriate energy-harvesting technique for human implantable sensors is still challenging for the industry where keen decisions have to be performed. Moreover, the available polymeric-based composite materials are offering plentiful renewable applications that can help sustainable development as being useful for the energy-harvesting systems such as photovoltaic, piezoelectric, thermoelectric devices as well as other energy storage systems. This work presents an expert-based model capable of better evaluating and examining various available renewable energy-harvesting techniques in urban surroundings subject to various technical and economic, often conflicting, criteria. Wide evaluation criteria have been adopted in the proposed model after examining their suitability as well as ensuring the expediency and reliability of the model by worldwide experts' feedback. The model includes establishing an analytic hierarchy structure with simultaneous 12 conflicting factors to establish a systematic road map for designers to better assess such techniques for human implantable medical sensors. The energy-harvesting techniques considered were limited to Wireless, Thermoelectric, Infrared Radiator, Piezoelectric, Magnetic Induction and Electrostatic Energy Harvesters. Results have demonstrated that the best decision was in favour of wireless-harvesting technology for the medical sensors as it is preferable by most of the considered evaluation criteria in the model.

Decision support system and medical liability.

PubMed Central

Allaërt, F. A.; Dusserre, L.

1992-01-01

Expert systems, which are going to be an essential tool in Medicine, are evolving in terms of sophistication of both knowledge representation and types of reasoning models used. The more efficient they are, the more often they will be used and professional liability will be involved. So after giving a short survey of configuration and working of expert systems, the authors will study the liabilities of people building and the using expert systems regarding some various dysfunctions. Of course the expert systems have to be considered only for human support and they should not possess any authority themselves, therefore the doctors must keep in mind that it is their own responsibility and as such keep their judgment and criticism. However other professionals could be involved, if they have participated in the building of expert systems. The different liabilities and the burden of proof are discussed according to some possible dysfunctions. In any case the final proof is inside the expert system by itself through re-computation of data. PMID:1482972

Decision-Making Phenomena Described by Expert Nurses Working in Urban Community Health Settings.

ERIC Educational Resources Information Center

Watkins, Mary P.

1998-01-01

Expert community health nurses (n=28) described crucial clinical situations. Content analysis revealed that decision making was both rational and intuitive. Eight themes were identified: decision-making focus, type, purpose, decision-maker characteristics, sequencing of events, data collection methods, facilitators/barriers, and decision-making…

Decision Analysis Methods Used to Make Appropriate Investments in Human Exploration Capabilities and Technologies

NASA Technical Reports Server (NTRS)

Williams-Byrd, Julie; Arney, Dale C.; Hay, Jason; Reeves, John D.; Craig, Douglas

2016-01-01

NASA is transforming human spaceflight. The Agency is shifting from an exploration-based program with human activities in low Earth orbit (LEO) and targeted robotic missions in deep space to a more sustainable and integrated pioneering approach. Through pioneering, NASA seeks to address national goals to develop the capacity for people to work, learn, operate, live, and thrive safely beyond Earth for extended periods of time. However, pioneering space involves daunting technical challenges of transportation, maintaining health, and enabling crew productivity for long durations in remote, hostile, and alien environments. Prudent investments in capability and technology developments, based on mission need, are critical for enabling a campaign of human exploration missions. There are a wide variety of capabilities and technologies that could enable these missions, so it is a major challenge for NASA's Human Exploration and Operations Mission Directorate (HEOMD) to make knowledgeable portfolio decisions. It is critical for this pioneering initiative that these investment decisions are informed with a prioritization process that is robust and defensible. It is NASA's role to invest in targeted technologies and capabilities that would enable exploration missions even though specific requirements have not been identified. To inform these investments decisions, NASA's HEOMD has supported a variety of analysis activities that prioritize capabilities and technologies. These activities are often based on input from subject matter experts within the NASA community who understand the technical challenges of enabling human exploration missions. This paper will review a variety of processes and methods that NASA has used to prioritize and rank capabilities and technologies applicable to human space exploration. The paper will show the similarities in the various processes and showcase instances were customer specified priorities force modifications to the process. Specifically, this paper will describe the processes that the NASA Langley Research Center (LaRC) Technology Assessment and Integration Team (TAIT) has used for several years and how those processes have been customized to meet customer needs while staying robust and defensible. This paper will show how HEOMD uses these analyses results to assist with making informed portfolio investment decisions. The paper will also highlight which human exploration capabilities and technologies typically rank high regardless of the specific design reference mission. The paper will conclude by describing future capability and technology ranking activities that will continue o leverage subject matter experts (SME) input while also incorporating more model-based analysis.

A Delphi-Based Framework for systems architecting of in-orbit exploration infrastructure for human exploration beyond Low Earth Orbit

NASA Astrophysics Data System (ADS)

Aliakbargolkar, Alessandro; Crawley, Edward F.

2014-01-01

The current debate in the U.S. Human Spaceflight Program focuses on the development of the next generation of man-rated heavy lift launch vehicles. While launch vehicle systems are of critical importance for future exploration, a comprehensive analysis of the entire exploration infrastructure is required to avoid costly pitfalls at early stages of the design process. This paper addresses this need by presenting a Delphi-Based Systems Architecting Framework for integrated architectural analysis of future in-orbit infrastructure for human space exploration beyond Low Earth Orbit. The paper is structured in two parts. The first part consists of an expert elicitation study to identify objectives for the in-space transportation infrastructure. The study was conducted between November 2011 and January 2012 with 15 senior experts involved in human spaceflight in the United States and Europe. The elicitation study included the formation of three expert panels representing exploration, science, and policy stakeholders engaged in a 3-round Delphi study. The rationale behind the Delphi approach, as imported from social science research, is discussed. Finally, a novel version of the Delphi method is presented and applied to technical decision-making and systems architecting in the context of human space exploration. The second part of the paper describes a tradespace exploration study of in-orbit infrastructure coupled with a requirements definition exercise informed by expert elicitation. The uncertainties associated with technical requirements and stakeholder goals are explicitly considered in the analysis. The outcome of the expert elicitation process portrays an integrated view of perceived stakeholder needs within the human spaceflight community. Needs are subsequently converted into requirements and coupled to the system architectures of interest to analyze the correlation between exploration, science, and policy goals. Pareto analysis is used to identify architectures of interest for further consideration by decision-makers. The paper closes with a summary of insights and develops a strategy for evolutionary development of the exploration infrastructure of the incoming decades. The most important result produced by this analysis is the identification of a critical irreducible ambiguity undermining value delivery for the in-space transportation infrastructure of the next three decades: destination choice. Consensus on destination is far from being reached by the community at large, with particular reference to exploration and policy stakeholders. The realization of this ambiguity is a call for NASA to promote an open forum on this topic, and to develop a strong case for policy makers to incentivize investments in the human spaceflight industry in the next decades.

Software for rapid prototyping in the pharmaceutical and biotechnology industries.

PubMed

Kappler, Michael A

2008-05-01

The automation of drug discovery methods continues to develop, especially techniques that process information, represent workflow and facilitate decision-making. The magnitude of data and the plethora of questions in pharmaceutical and biotechnology research give rise to the need for rapid prototyping software. This review describes the advantages and disadvantages of three solutions: Competitive Workflow, Taverna and Pipeline Pilot. Each of these systems processes large amounts of data, integrates diverse systems and assists novice programmers and human experts in critical decision-making steps.

Reliability of the MDi Psoriasis® Application to Aid Therapeutic Decision-Making in Psoriasis.

PubMed

Moreno-Ramírez, D; Herrerías-Esteban, J M; Ojeda-Vila, T; Carrascosa, J M; Carretero, G; de la Cueva, P; Ferrándiz, C; Galán, M; Rivera, R; Rodríguez-Fernández, L; Ruiz-Villaverde, R; Ferrándiz, L

2017-09-01

Therapeutic decisions in psoriasis are influenced by disease factors (e.g., severity or location), comorbidity, and demographic and clinical features. We aimed to assess the reliability of a mobile telephone application (MDi-Psoriasis) designed to help the dermatologist make decisions on how to treat patients with moderate to severe psoriasis. We analyzed interobserver agreement between the advice given by an expert panel and the recommendations of the MDi-Psoriasis application in 10 complex cases of moderate to severe psoriasis. The experts were asked their opinion on which treatments were most appropriate, possible, or inappropriate. Data from the same 10 cases were entered into the MDi-Psoriasis application. Agreement was analyzed in 3 ways: paired interobserver concordance (Cohen's κ), multiple interobserver concordance (Fleiss's κ), and percent agreement between recommendations. The mean percent agreement between the total of 1210 observations was 51.3% (95% CI, 48.5-54.1%). Cohen's κ statistic was 0.29 and Fleiss's κ was 0.28. Mean agreement between pairs of human observers only, excluding the MDi-Psoriasis recommendations, was 50.5% (95% CI, 47.6-53.5%). Paired agreement between the recommendations of the MDi-Psoriasis tool and the majority opinion of the expert panel (Cohen's κ) was 0.44 (68.2% agreement). The MDi-Psoriasis tool can generate recommendations that are comparable to those of experts in psoriasis. Copyright © 2017 AEDV. Publicado por Elsevier España, S.L.U. All rights reserved.

The influence of expert opinions on the selection of wastewater treatment alternatives: a group decision-making approach.

PubMed

Kalbar, Pradip P; Karmakar, Subhankar; Asolekar, Shyam R

2013-10-15

The application of multiple-attribute decision-making (MADM) to real life decision problems suggests that avoiding the loss of information through scenario-based approaches and including expert opinions in the decision-making process are two major challenges that require more research efforts. Recently, a wastewater treatment technology selection effort has been made with a 'scenario-based' method of MADM. This paper focuses on a novel approach to incorporate expert opinions into the scenario-based decision-making process, as expert opinions play a major role in the selection of treatment technologies. The sets of criteria and the indicators that are used consist of both qualitative and quantitative criteria. The group decision-making (GDM) approach that is implemented for aggregating expert opinions is based on an analytical hierarchy process (AHP), which is the most widely used MADM method. The pairwise comparison matrices (PCMs) for qualitative criteria are formed based on expert opinions, whereas, a novel approach is proposed for generating PCMs for quantitative criteria. It has been determined that the experts largely prefer natural treatment systems because they are more sustainable in any scenario. However, PCMs based on expert opinions suggest that advanced technologies such as the sequencing batch reactor (SBR) can also be appropriate for a given decision scenario. The proposed GDM approach is a rationalized process that will be more appropriate in realistic scenarios where multiple stakeholders with local and regional societal priorities are involved in the selection of treatment technology. Copyright © 2013 Elsevier Ltd. All rights reserved.

Expert Systems, Job Aids, and the Future of Instructional Technology; and Decision Tables, the Poor Person's Answer to "Expert Systems."

ERIC Educational Resources Information Center

Harmon, Paul; Pipe, Peter

1986-01-01

Describes design and presents examples of industrial use of small expert systems and guidelines for choosing problems which lend themselves to small tool solutions. Use of microcomputer facilitated decision tables to diagnose and categorize people, things, and issues is suggested, and development of three decision table formats is described. (MBR)

Conceptual Elaboration Sequencing: An External Validation Study in Nursing Education

ERIC Educational Resources Information Center

Kinderman, Kathy T.

2012-01-01

Nursing education is a knowledge domain that requires higher order thinking (critical thinking) for making decisions that impact outcomes of human health. The goal of nursing education is to develop novice experts in nursing knowledge and clinical practice. In order to achieve this goal, nursing education must employ instructional approaches that…

Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation

PubMed Central

Beijbom, Oscar; Edmunds, Peter J.; Roelfsema, Chris; Smith, Jennifer; Kline, David I.; Neal, Benjamin P.; Dunlap, Matthew J.; Moriarty, Vincent; Fan, Tung-Yung; Tan, Chih-Jui; Chan, Stephen; Treibitz, Tali; Gamst, Anthony; Mitchell, B. Greg; Kriegman, David

2015-01-01

Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys. PMID:26154157

Practical problems in aggregating expert opinions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Booker, J.M.; Picard, R.R.; Meyer, M.A.

1993-11-01

Expert opinion is data given by a qualified person in response to a technical question. In these analyses, expert opinion provides information where other data are either sparse or non-existent. Improvements in forecasting result from the advantageous addition of expert opinion to observed data in many areas, such as meteorology and econometrics. More generally, analyses of large, complex systems often involve experts on various components of the system supplying input to a decision process; applications include such wide-ranging areas as nuclear reactor safety, management science, and seismology. For large or complex applications, no single expert may be knowledgeable enough aboutmore » the entire application. In other problems, decision makers may find it comforting that a consensus or aggregation of opinions is usually better than a single opinion. Many risk and reliability studies require a single estimate for modeling, analysis, reporting, and decision making purposes. For problems with large uncertainties, the strategy of combining as diverse a set of experts as possible hedges against underestimation of that uncertainty. Decision makers are frequently faced with the task of selecting the experts and combining their opinions. However, the aggregation is often the responsibility of an analyst. Whether the decision maker or the analyst does the aggregation, the input for it, such as providing weights for experts or estimating other parameters, is imperfect owing to a lack of omniscience. Aggregation methods for expert opinions have existed for over thirty years; yet many of the difficulties with their use remain unresolved. The bulk of these problem areas are summarized in the sections that follow: sensitivities of results to assumptions, weights for experts, correlation of experts, and handling uncertainties. The purpose of this paper is to discuss the sources of these problems and describe their effects on aggregation.« less

Decision Support Systems for Launch and Range Operations Using Jess

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2007-01-01

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

A Statistical Evaluation of the Diagnostic Performance of MEDAS-The Medical Emergency Decision Assistance System

PubMed Central

Georgakis, D. Christine; Trace, David A.; Naeymi-Rad, Frank; Evens, Martha

1990-01-01

Medical expert systems require comprehensive evaluation of their diagnostic accuracy. The usefulness of these systems is limited without established evaluation methods. We propose a new methodology for evaluating the diagnostic accuracy and the predictive capacity of a medical expert system. We have adapted to the medical domain measures that have been used in the social sciences to examine the performance of human experts in the decision making process. Thus, in addition to the standard summary measures, we use measures of agreement and disagreement, and Goodman and Kruskal's λ and τ measures of predictive association. This methodology is illustrated by a detailed retrospective evaluation of the diagnostic accuracy of the MEDAS system. In a study using 270 patients admitted to the North Chicago Veterans Administration Hospital, diagnoses produced by MEDAS are compared with the discharge diagnoses of the attending physicians. The results of the analysis confirm the high diagnostic accuracy and predictive capacity of the MEDAS system. Overall, the agreement of the MEDAS system with the “gold standard” diagnosis of the attending physician has reached a 90% level.

Pilot/Controller Coordinated Decision Making in the Next Generation Air Transportation System

NASA Technical Reports Server (NTRS)

Bearman, Chris; Miller, Ronald c.; Orasanu, Judith M.

2011-01-01

Introduction: NextGen technologies promise to provide considerable benefits in terms of enhancing operations and improving safety. However, there needs to be a thorough human factors evaluation of the way these systems will change the way in which pilot and controllers share information. The likely impact of these new technologies on pilot/controller coordinated decision making is considered in this paper using the "operational, informational and evaluative disconnect" framework. Method: Five participant focus groups were held. Participants were four experts in human factors, between x and x research students and a technical expert. The participant focus group evaluated five key NextGen technologies to identify issues that made different disconnects more or less likely. Results: Issues that were identified were: Decision Making will not necessarily improve because pilots and controllers possess the same information; Having a common information source does not mean pilots and controllers are looking at the same information; High levels of automation may lead to disconnects between the technology and pilots/controllers; Common information sources may become the definitive source for information; Overconfidence in the automation may lead to situations where appropriate breakdowns are not initiated. Discussion: The issues that were identified lead to recommendations that need to be considered in the development of NextGen technologies. The current state of development of these technologies provides a good opportunity to utilize recommendations at an early stage so that NextGen technologies do not lead to difficulties in resolving breakdowns in coordinated decision making.

Expert and non-expert knowledge in medical practice.

PubMed

Nordin, I

2000-01-01

One problematic aspect of the rationality of medical practice concerns the relation between expert knowledge and non-expert knowledge. In medical practice it is important to match medical knowledge with the self-knowledge of the individual patient. This paper tries to study the problem of such matching by describing a model for technological paradigms and comparing it with an ideal of technological rationality. The professionalised experts tend to base their decisions and actions mostly on medical knowledge while the rationality of medicine also involves just as important elements of the personal evaluation and knowledge of the patients. Since both types of knowledge are necessary for rational decisions, the gap between the expert and the non-expert has to be bridged in some way. A solution to the problem is suggested in terms of pluralism, with the patient as ultimate decision-maker.

Hemispheric Activation Differences in Novice and Expert Clinicians during Clinical Decision Making

ERIC Educational Resources Information Center

Hruska, Pam; Hecker, Kent G.; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Krigolson, Olav

2016-01-01

Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience…

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.; Lea, Robert N.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. Simply stated, the problem reduces to the following: how can we capture the knowledge of an expert when the expert is unable to clearly formulate how he or she arrives at a decision? A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision may have been made. Unique to our work is the fuzzy set representation of the conditions or attributes upon which the expert may possibly base his fuzzy decision. From our examples, we infer certain and possible fuzzy rules for closing a customer service center and illustrate the importance of having the decision closely relate to the conditions under consideration.

Advances on a Decision Analytic Approach to Exposure-Based Chemical Prioritization.

PubMed

Wood, Matthew D; Plourde, Kenton; Larkin, Sabrina; Egeghy, Peter P; Williams, Antony J; Zemba, Valerie; Linkov, Igor; Vallero, Daniel A

2018-05-11

The volume and variety of manufactured chemicals is increasing, although little is known about the risks associated with the frequency and extent of human exposure to most chemicals. The EPA and the recent signing of the Lautenberg Act have both signaled the need for high-throughput methods to characterize and screen chemicals based on exposure potential, such that more comprehensive toxicity research can be informed. Prior work of Mitchell et al. using multicriteria decision analysis tools to prioritize chemicals for further research is enhanced here, resulting in a high-level chemical prioritization tool for risk-based screening. Reliable exposure information is a key gap in currently available engineering analytics to support predictive environmental and health risk assessments. An elicitation with 32 experts informed relative prioritization of risks from chemical properties and human use factors, and the values for each chemical associated with each metric were approximated with data from EPA's CP_CAT database. Three different versions of the model were evaluated using distinct weight profiles, resulting in three different ranked chemical prioritizations with only a small degree of variation across weight profiles. Future work will aim to include greater input from human factors experts and better define qualitative metrics. © 2018 Society for Risk Analysis.

Expert-novice differences in cognitive and execution skills during tennis competition.

PubMed

Del Villar, Fernando; García González, Luis; Iglesias, Damián; Perla Moreno, M; Cervelló, Eduardo M

2007-04-01

This study deals with decision and execution behavior of tennis players during competition. The study is based on the expert-novice paradigm and aims to identify differences between both groups in the decision-making and execution variables in serve and shot actions in tennis. Six expert players (elite Spanish tennis players) and six novice players (grade school tennis players) took part in this study. To carry out this study, the observation protocol defined by McPherson and Thomas in 1989, in which control, decision-making and execution variables were included, was used, where it was applied to the performance of the tennis player in a real match situation. In the analysis, significant differences between experts and novices in decision-making and execution variables are found wherein it can be observed that experts display a greater ability to make the appropriate decisions, selecting the most tactical responses to put pressure on the opponent. Expert tennis players were also able to carry out forceful executions to their opponent with greater efficiency, making the opponent's response to a large extent more difficult. These findings are in accordance with those of McPherson and colleagues.

Human factors of intelligent computer aided display design

NASA Technical Reports Server (NTRS)

Hunt, R. M.

1985-01-01

Design concepts for a decision support system being studied at NASA Langley as an aid to visual display unit (VDU) designers are described. Ideally, human factors should be taken into account by VDU designers. In reality, although the human factors database on VDUs is small, such systems must be constantly developed. Human factors are therefore a secondary consideration. An expert system will thus serve mainly in an advisory capacity. Functions can include facilitating the design process by shortening the time to generate and alter drawings, enhancing the capability of breaking design requirements down into simpler functions, and providing visual displays equivalent to the final product. The VDU system could also discriminate, and display the difference, between designer decisions and machine inferences. The system could also aid in analyzing the effects of designer choices on future options and in ennunciating when there are data available on a design selections.

Wishful Thinking? Inside the Black Box of Exposure Assessment.

PubMed

Money, Annemarie; Robinson, Christine; Agius, Raymond; de Vocht, Frank

2016-05-01

Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts' assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the 'black box' of exposure assessment. A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; 'intensity'; 'probability'; 'agent'; 'process'; and 'duration' of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Health care workers and their needs: the forgotten shadow of AIM research.

PubMed

Lillehaug, S I; Lajoie, S

1998-01-01

The field of AI in Medicine (AIM) seems to have accepted that decision support is, and will be, needed within most medical domains. As society calls for cost-effectiveness, and human expertise or expert guidance are not always available, decision support systems (DSSs) are proposed as the solutions. These solutions, however, do not necessarily correspond with the basic needs of their targeted users. We will show this through a review of the literature related to health care workers and the various factors that have an influence on their performances. Furthermore, we will use these empirical findings to argue that the AIM community must go beyond its decision support philosophy, whereby the gaps in human expertise are filled in by the computer. In the future, joint emphasis must be placed on decision support and the promotion towards independent and self-sufficient problem solving. In order to implement this paradigm change, the AIM community will have to incorporate findings from the research discipline of AI in Education.

Informing Public Perceptions About Climate Change: A 'Mental Models' Approach.

PubMed

Wong-Parodi, Gabrielle; Bruine de Bruin, Wändi

2017-10-01

As the specter of climate change looms on the horizon, people will face complex decisions about whether to support climate change policies and how to cope with climate change impacts on their lives. Without some grasp of the relevant science, they may find it hard to make informed decisions. Climate experts therefore face the ethical need to effectively communicate to non-expert audiences. Unfortunately, climate experts may inadvertently violate the maxims of effective communication, which require sharing communications that are truthful, brief, relevant, clear, and tested for effectiveness. Here, we discuss the 'mental models' approach towards developing communications, which aims to help experts to meet the maxims of effective communications, and to better inform the judgments and decisions of non-expert audiences.

Defining decision making: a qualitative study of international experts' views on surgical trainee decision making.

PubMed

Rennie, Sarah C; van Rij, Andre M; Jaye, Chrystal; Hall, Katherine H

2011-06-01

Decision making is a key competency of surgeons; however, how best to assess decisions and decision makers is not clearly established. The aim of the present study was to identify criteria that inform judgments about surgical trainees' decision-making skills. A qualitative free text web-based survey was distributed to recognized international experts in Surgery, Medical Education, and Cognitive Research. Half the participants were asked to identify features of good decisions, characteristics of good decision makers, and essential factors for developing good decision-making skills. The other half were asked to consider these areas in relation to poor decision making. Template analysis of free text responses was performed. Twenty-nine (52%) experts responded to the survey, identifying 13 categories for judging a decision and 14 for judging a decision maker. Twelve features/characteristics overlapped (considered, informed, well timed, aware of limitations, communicated, knowledgeable, collaborative, patient-focused, flexible, able to act on the decision, evidence-based, and coherent). Fifteen categories were generated for essential factors leading to development of decision-making skills that fall into three major themes (personal qualities, training, and culture). The categories compiled from the perspectives of good/poor were predominantly the inverse of each other; however, the weighting given to some categories varied. This study provides criteria described by experts when considering surgical decisions, decision makers, and development of decision-making skills. It proposes a working definition of a good decision maker. Understanding these criteria will enable clinical teachers to better recognize and encourage good decision-making skills and identify poor decision-making skills for remediation.

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert

PubMed Central

Schmidt, Henk G.; Rikers, Remy M. J. P.; Custers, Eugene J. F. M.; Splinter, Ted A. W.; van Saase, Jan L. C. M.

2010-01-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices’ decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases. PMID:20354726

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert.

PubMed

Mamede, Sílvia; Schmidt, Henk G; Rikers, Remy M J P; Custers, Eugene J F M; Splinter, Ted A W; van Saase, Jan L C M

2010-11-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices' decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases.

Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

PubMed

Sheikhtaheri, Abbas; Sadoughi, Farahnaz; Hashemi Dehaghi, Zahra

2014-09-01

Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision was made. Unique to this work is the fuzzy set representation of the conditions or attributes upon which the decision make may base his fuzzy set decision. From our examples, we infer certain and possible rules containing fuzzy terms. It should be stressed that the procedure determines how closely the expert follows the conditions under consideration in making his decision. We offer two examples pertaining to the possible decision to close a customer service center of a public utility company. In the first example, the decision maker does not follow too closely the conditions. In the second example, the conditions are much more relevant to the decision of the expert.

How do expert soccer players encode visual information to make decisions in simulated game situations?

PubMed

Poplu, Gérald; Ripoll, Hubert; Mavromatis, Sébastien; Baratgin, Jean

2008-09-01

The aim of this study was to determine what visual information expert soccer players encode when they are asked to make a decision. We used a repetition-priming paradigm to test the hypothesis that experts encode a soccer pattern's structure independently of the players' physical characteristics (i.e., posture and morphology). The participants were given either realistic (digital photos) or abstract (three-dimensional schematic representations) soccer game patterns. The results showed that the experts benefited from priming effects regardless of how abstract the stimuli were. This suggests that an abstract representation of a realistic pattern (i.e., one that does not include visual information related to the players'physical characteristics) is sufficient to activate experts'specific knowledge during decision making. These results seem to show that expert soccer players encode and store abstract representations of visual patterns in memory.

Research on filter’s parameter selection based on PROMETHEE method

NASA Astrophysics Data System (ADS)

Zhu, Hui-min; Wang, Hang-yu; Sun, Shi-yan

2018-03-01

The selection of filter’s parameters in target recognition was studied in this paper. The PROMETHEE method was applied to the optimization problem of Gabor filter parameters decision, the correspondence model of the elemental relation between two methods was established. The author took the identification of military target as an example, problem about the filter’s parameter decision was simulated and calculated by PROMETHEE. The result showed that using PROMETHEE method for the selection of filter’s parameters was more scientific. The human disturbance caused by the experts method and empirical method could be avoided by this way. The method can provide reference for the parameter configuration scheme decision of the filter.

A pathway to personalization of integrated treatment: informatics and decision science in psychiatric rehabilitation.

PubMed

Spaulding, William; Deogun, Jitender

2011-09-01

Personalization of treatment is a current strategic goal for improving health care. Integrated treatment approaches such as psychiatric rehabilitation benefit from personalization because they involve matching diverse arrays of treatment options to individually unique profiles of need. The need for personalization is evident in the heterogeneity of people with severe mental illness and in the findings of experimental psychopathology. One pathway to personalization lies in analysis of the judgments and decision making of human experts and other participants as they respond to complex circumstances in pursuit of treatment and rehabilitation goals. Such analysis is aided by computer simulation of human decision making, which in turn informs development of computerized clinical decision support systems. This inspires a research program involving concurrent development of databases, domain ontology, and problem-solving algorithms, toward the goal of personalizing psychiatric rehabilitation through human collaboration with intelligent cyber systems. The immediate hurdle is to demonstrate that clinical decisions beyond diagnosis really do affect outcome. This can be done by supporting the hypothesis that a human treatment team with access to a reasonably comprehensive clinical database that tracks patient status and treatment response over time achieves better outcome than a treatment team without such access, in a controlled experimental trial. Provided the hypothesis can be supported, the near future will see prototype systems that can construct an integrated assessment, formulation, and rehabilitation plan from clinical assessment data and contextual information. This will lead to advanced systems that collaborate with human decision makers to personalize psychiatric rehabilitation and optimize outcome.

The medical decision model and decision maker tools for management of radiological and nuclear incidents.

PubMed

Koerner, John F; Coleman, C Norman; Murrain-Hill, Paula; FitzGerald, Denis J; Sullivan, Julie M

2014-06-01

Effective decision making during a rapidly evolving emergency such as a radiological or nuclear incident requires timely interim decisions and communications from onsite decision makers while further data processing, consultation, and review are ongoing by reachback experts. The authors have recently proposed a medical decision model for use during a radiological or nuclear disaster, which is similar in concept to that used in medical care, especially when delay in action can have disastrous effects. For decision makers to function most effectively during a complex response, they require access to onsite subject matter experts who can provide information, recommendations, and participate in public communication efforts. However, in the time before this expertise is available or during the planning phase, just-in-time tools are essential that provide critical overview of the subject matter written specifically for the decision makers. Recognizing the complexity of the science, risk assessment, and multitude of potential response assets that will be required after a nuclear incident, the Office of the Assistant Secretary for Preparedness and Response, in collaboration with other government and non-government experts, has prepared a practical guide for decision makers. This paper illustrates how the medical decision model process could facilitate onsite decision making that includes using the deliberative reachback process from science and policy experts and describes the tools now available to facilitate timely and effective incident management.

Is the relationship between pattern recall and decision-making influenced by anticipatory recall?

PubMed

Gorman, Adam D; Abernethy, Bruce; Farrow, Damian

2013-01-01

The present study compared traditional measures of pattern recall to measures of anticipatory recall and decision-making to examine the underlying mechanisms of expert pattern perception and to address methodological limitations in previous studies where anticipatory recall has generally been overlooked. Recall performance in expert and novice basketball players was measured by examining the spatial error in recalling player positions both for a target image (traditional recall) and at 40-ms increments following the target image (anticipatory recall). Decision-making performance was measured by comparing the participant's response to those identified by a panel of expert coaches. Anticipatory recall was observed in the recall task and was significantly more pronounced for the experts, suggesting that traditional methods of spatial recall analysis may not have provided a completely accurate determination of the full magnitude of the experts' superiority. Accounting for anticipatory recall also increased the relative contribution of recall skill to decision-making accuracy although the gains in explained variance were modest and of debatable functional significance.

Wishful Thinking? Inside the Black Box of Exposure Assessment

PubMed Central

Money, Annemarie; Robinson, Christine; Agius, Raymond; de Vocht, Frank

2016-01-01

Background: Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts’ assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the ‘black box’ of exposure assessment. Methods: A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Results: Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; ‘intensity’; ‘probability’; ‘agent’; ‘process’; and ‘duration’ of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. Conclusion: In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment. PMID:26764244

Objective Assessment of the Interfrontal Angle for Severity Grading and Operative Decision-Making in Metopic Synostosis.

PubMed

Anolik, Rachel A; Allori, Alexander C; Pourtaheri, Navid; Rogers, Gary F; Marcus, Jeffrey R

2016-05-01

The purpose of this study was to evaluate the utility of a previously validated interfrontal angle for classification of severity of metopic synostosis and as an aid to operative decision-making. An expert panel was asked to study 30 cases ranging from minor to severe metopic synostosis. Based on computed tomographic images of the skull and clinical photographs, they classified the severity of trigonocephaly (1 = normal, 2 = mild, 3 = moderate, and 4 = severe) and management (0 = nonoperative and 1 = operative). The severity scores and management reported by experts were then pooled and matched with the interfrontal angle computed from each respective computed tomographic scan. A threshold was identified at which most experts agree on operative management. Expert severity scores were higher for more acute interfrontal angles. There was a high concordance at the extremes of classifications, severe (4) and normal (1) (p < 0.0001); however, between interfrontal angles of 114.3 and 136.1 degrees, there exists a "gray zone," with severe discordance in expert rankings. An operative threshold of 118.2 degrees was identified, with the interfrontal angle able to predict the expert panel's decision to proceed with surgery 87.6 percent of the time. The interfrontal angle has been previously validated as a simple, accurate, and reproducible means for diagnosing trigonocephaly, but must be obtained from computed tomographic data. In this article, the authors demonstrate that the interfrontal angle can be used to further characterize the severity of trigonocephaly. It also correlated with expert decision-making for operative versus nonoperative management. This tool may be used as an adjunct to clinical decision-making when the decision to proceed with surgery may not be straightforward. Diagnostic, V.

AutoNR: an automated system that measures ECAP thresholds with the Nucleus Freedom cochlear implant via machine intelligence.

PubMed

Botros, Andrew; van Dijk, Bas; Killian, Matthijs

2007-05-01

AutoNRT is an automated system that measures electrically evoked compound action potential (ECAP) thresholds from the auditory nerve with the Nucleus Freedom cochlear implant. ECAP thresholds along the electrode array are useful in objectively fitting cochlear implant systems for individual use. This paper provides the first detailed description of the AutoNRT algorithm and its expert systems, and reports the clinical success of AutoNRT to date. AutoNRT determines thresholds by visual detection, using two decision tree expert systems that automatically recognise ECAPs. The expert systems are guided by a dataset of 5393 neural response measurements. The algorithm approaches threshold from lower stimulus levels, ensuring recipient safety during postoperative measurements. Intraoperative measurements use the same algorithm but proceed faster by beginning at stimulus levels much closer to threshold. When searching for ECAPs, AutoNRT uses a highly specific expert system (specificity of 99% during training, 96% during testing; sensitivity of 91% during training, 89% during testing). Once ECAPs are established, AutoNRT uses an unbiased expert system to determine an accurate threshold. Throughout the execution of the algorithm, recording parameters (such as implant amplifier gain) are automatically optimised when needed. In a study that included 29 intraoperative and 29 postoperative subjects (a total of 418 electrodes), AutoNRT determined a threshold in 93% of cases where a human expert also determined a threshold. When compared to the median threshold of multiple human observers on 77 randomly selected electrodes, AutoNRT performed as accurately as the 'average' clinician. AutoNRT has demonstrated a high success rate and a level of performance that is comparable with human experts. It has been used in many clinics worldwide throughout the clinical trial and commercial launch of Nucleus Custom Sound Suite, significantly streamlining the clinical procedures associated with cochlear implant use.

How Do Expert Soccer Players Encode Visual Information to Make Decisions in Simulated Game Situations?

ERIC Educational Resources Information Center

Poplu, Gerald; Ripoll, Hubert; Mavromatis, Sebastien; Baratgin, Jean

2008-01-01

The aim of this study was to determine what visual information expert soccer players encode when they are asked to make a decision. We used a repetition-priming paradigm to test the hypothesis that experts encode a soccer pattern's structure independently of the players' physical characteristics (i.e., posture and morphology). The participants…

Models Used to Select Strategic Planning Experts for High Technology Productions

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Grigorjeva, Antonina A.; Tseplit, Anna P.; Ozgogov, Evgenij V.

2016-04-01

The article deals with the problems and specific aspects in organizing works of experts involved in assessment of companies that manufacture complex high-technology products. A model is presented that is intended for evaluating competences of experts in individual functional areas of expertise. Experts are selected to build a group on the basis of tables used to determine a competence level. An expert selection model based on fuzzy logic is proposed and additional requirements for the expert group composition can be taken into account, with regard to the needed quality and competence related preferences of decision-makers. A Web-based information system model is developed for the interaction between experts and decision-makers when carrying out online examinations.

Fuzzy Expert System for Heart Attack Diagnosis

NASA Astrophysics Data System (ADS)

Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

2017-08-01

Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

Computer-based diagnostic expert systems in rheumatology: where do we stand in 2014?

PubMed

Alder, Hannes; Michel, Beat A; Marx, Christian; Tamborrini, Giorgio; Langenegger, Thomas; Bruehlmann, Pius; Steurer, Johann; Wildi, Lukas M

2014-01-01

Background. The early detection of rheumatic diseases and the treatment to target have become of utmost importance to control the disease and improve its prognosis. However, establishing a diagnosis in early stages is challenging as many diseases initially present with similar symptoms and signs. Expert systems are computer programs designed to support the human decision making and have been developed in almost every field of medicine. Methods. This review focuses on the developments in the field of rheumatology to give a comprehensive insight. Medline, Embase, and Cochrane Library were searched. Results. Reports of 25 expert systems with different design and field of application were found. The performance of 19 of the identified expert systems was evaluated. The proportion of correctly diagnosed cases was between 43.1 and 99.9%. Sensitivity and specificity ranged from 62 to 100 and 88 to 98%, respectively. Conclusions. Promising diagnostic expert systems with moderate to excellent performance were identified. The validation process was in general underappreciated. None of the systems, however, seemed to have succeeded in daily practice. This review identifies optimal characteristics to increase the survival rate of expert systems and may serve as valuable information for future developments in the field.

Inside the black box: starting to uncover the underlying decision rules used in one-by-one expert assessment of occupational exposure in case-control studies

PubMed Central

Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Yu, Kai; Shortreed, Susan M.; Pronk, Anjoeka; Stewart, Patricia A.; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Silverman, Debra T.; Friesen, Melissa C.

2014-01-01

Objectives Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participants' reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time-consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review, and future use of these expert-based exposure decisions. Methods Classification and regression trees (CART, predictions from a single tree) and random forests (predictions from many trees) were used to identify the underlying rules from the questionnaire responses and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity, and frequency. Data were split into training (n=10,488 jobs), testing (n=2,247), and validation (n=2,248) data sets. Results The CART and random forest models' predictions agreed with 92–94% of the expert's binary probability assignments. For ordinal probability, intensity, and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86–90% and 57–85%, respectively) than for low or medium exposed jobs (7–71%). Conclusions CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent and creates a mechanism to efficiently replicate exposure decisions in future studies. PMID:23155187

Expert Financial Advice Neurobiologically “Offloads” Financial Decision-Making under Risk

PubMed Central

Engelmann, Jan B.; Capra, C. Monica; Noussair, Charles; Berns, Gregory S.

2009-01-01

Background Financial advice from experts is commonly sought during times of uncertainty. While the field of neuroeconomics has made considerable progress in understanding the neurobiological basis of risky decision-making, the neural mechanisms through which external information, such as advice, is integrated during decision-making are poorly understood. In the current experiment, we investigated the neurobiological basis of the influence of expert advice on financial decisions under risk. Methodology/Principal Findings While undergoing fMRI scanning, participants made a series of financial choices between a certain payment and a lottery. Choices were made in two conditions: 1) advice from a financial expert about which choice to make was displayed (MES condition); and 2) no advice was displayed (NOM condition). Behavioral results showed a significant effect of expert advice. Specifically, probability weighting functions changed in the direction of the expert's advice. This was paralleled by neural activation patterns. Brain activations showing significant correlations with valuation (parametric modulation by value of lottery/sure win) were obtained in the absence of the expert's advice (NOM) in intraparietal sulcus, posterior cingulate cortex, cuneus, precuneus, inferior frontal gyrus and middle temporal gyrus. Notably, no significant correlations with value were obtained in the presence of advice (MES). These findings were corroborated by region of interest analyses. Neural equivalents of probability weighting functions showed significant flattening in the MES compared to the NOM condition in regions associated with probability weighting, including anterior cingulate cortex, dorsolateral PFC, thalamus, medial occipital gyrus and anterior insula. Finally, during the MES condition, significant activations in temporoparietal junction and medial PFC were obtained. Conclusions/Significance These results support the hypothesis that one effect of expert advice is to “offload” the calculation of value of decision options from the individual's brain. PMID:19308261

One Health: a perspective from the human health sector.

PubMed

Kakkar, M; Hossain, S S; Abbas, S S

2014-08-01

Despite emerging consensus that the One Health concept involves multiple stakeholders, the human health sector has continued to view it from a predominantly human health security perspective. It has often ignored the concerns of other sectors, e.g. concerns that relate to trade, commerce, livelihoods and sustainable development, all of which are important contributors to societal well-being. In the absence of a culture of collaboration, clear One Health goals, conceptual clarity and operating frameworks, this disconnect between human health and One Health efforts has often impeded the translation of One Health from concept to reality, other than during emergency situations. If there are to be effective and sustainable One Health partnerships we must identify clear operating principles that allow flexible approaches to intersectoral collaborations. To convince technical experts and political leaders in the human health sector of the importance of intersectoral cooperation, and to make the necessary structural adjustments, we need examples of best practice models and trans-sectoral methods for measuring the risks, burden and costs across sectors. Informal collaborations between researchers and technical experts will play a decisive role in developing these methods and models and instilling societal well-being into the human health sector's view of One Health.

The role of the insula in intuitive expert bug detection in computer code: an fMRI study.

PubMed

Castelhano, Joao; Duarte, Isabel C; Ferreira, Carlos; Duraes, Joao; Madeira, Henrique; Castelo-Branco, Miguel

2018-05-09

Software programming is a complex and relatively recent human activity, involving the integration of mathematical, recursive thinking and language processing. The neural correlates of this recent human activity are still poorly understood. Error monitoring during this type of task, requiring the integration of language, logical symbol manipulation and other mathematical skills, is particularly challenging. We therefore aimed to investigate the neural correlates of decision-making during source code understanding and mental manipulation in professional participants with high expertise. The present fMRI study directly addressed error monitoring during source code comprehension, expert bug detection and decision-making. We used C code, which triggers the same sort of processing irrespective of the native language of the programmer. We discovered a distinct role for the insula in bug monitoring and detection and a novel connectivity pattern that goes beyond the expected activation pattern evoked by source code understanding in semantic language and mathematical processing regions. Importantly, insula activity levels were critically related to the quality of error detection, involving intuition, as signalled by reported initial bug suspicion, prior to final decision and bug detection. Activity in this salience network (SN) region evoked by bug suspicion was predictive of bug detection precision, suggesting that it encodes the quality of the behavioral evidence. Connectivity analysis provided evidence for top-down circuit "reutilization" stemming from anterior cingulate cortex (BA32), a core region in the SN that evolved for complex error monitoring such as required for this type of recent human activity. Cingulate (BA32) and anterolateral (BA10) frontal regions causally modulated decision processes in the insula, which in turn was related to activity of math processing regions in early parietal cortex. In other words, earlier brain regions used during evolution for other functions seem to be reutilized in a top-down manner for a new complex function, in an analogous manner as described for other cultural creations such as reading and literacy.

Incorporation of expert variability into breast cancer treatment recommendation in designing clinical protocol guided fuzzy rule system models.

PubMed

Garibaldi, Jonathan M; Zhou, Shang-Ming; Wang, Xiao-Ying; John, Robert I; Ellis, Ian O

2012-06-01

It has been often demonstrated that clinicians exhibit both inter-expert and intra-expert variability when making difficult decisions. In contrast, the vast majority of computerized models that aim to provide automated support for such decisions do not explicitly recognize or replicate this variability. Furthermore, the perfect consistency of computerized models is often presented as a de facto benefit. In this paper, we describe a novel approach to incorporate variability within a fuzzy inference system using non-stationary fuzzy sets in order to replicate human variability. We apply our approach to a decision problem concerning the recommendation of post-operative breast cancer treatment; specifically, whether or not to administer chemotherapy based on assessment of five clinical variables: NPI (the Nottingham Prognostic Index), estrogen receptor status, vascular invasion, age and lymph node status. In doing so, we explore whether such explicit modeling of variability provides any performance advantage over a more conventional fuzzy approach, when tested on a set of 1310 unselected cases collected over a fourteen year period at the Nottingham University Hospitals NHS Trust, UK. The experimental results show that the standard fuzzy inference system (that does not model variability) achieves overall agreement to clinical practice around 84.6% (95% CI: 84.1-84.9%), while the non-stationary fuzzy model can significantly increase performance to around 88.1% (95% CI: 88.0-88.2%), p<0.001. We conclude that non-stationary fuzzy models provide a valuable new approach that may be applied to clinical decision support systems in any application domain. Copyright © 2012 Elsevier Inc. All rights reserved.

Analysis of methods of processing of expert information by optimization of administrative decisions

NASA Astrophysics Data System (ADS)

Churakov, D. Y.; Tsarkova, E. G.; Marchenko, N. D.; Grechishnikov, E. V.

2018-03-01

In the real operation the measure definition methodology in case of expert estimation of quality and reliability of application-oriented software products is offered. In operation methods of aggregation of expert estimates on the example of a collective choice of an instrumental control projects in case of software development of a special purpose for needs of institutions are described. Results of operation of dialogue decision making support system are given an algorithm of the decision of the task of a choice on the basis of a method of the analysis of hierarchies and also. The developed algorithm can be applied by development of expert systems to the solution of a wide class of the tasks anyway connected to a multicriteria choice.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Astrophysics Data System (ADS)

Szatkowski, Gerard P.; Schultz, Roger

1988-11-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Technical Reports Server (NTRS)

Szatkowski, Gerard P.; Schultz, Roger

1988-01-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

Call-duration and triage decisions in out of hours cooperatives with and without the use of an expert system.

PubMed

Ong, Rob S G; Post, Johan; van Rooij, Harry; de Haan, Jan

2008-02-13

Cooperatives delivering out of hours care in the Netherlands are hesitant about the use of expert systems during triage. Apart from the extra costs, cooperatives are not sure that quality of triage is sufficiently enhanced by these systems and believe that call duration will be prolonged drastically. No figures about the influence of the use of an expert system during triage on call duration and triage decisions in out of hours care in the Netherlands are available. Electronically registered data concerning call duration and triage decisions were collected in two cooperatives. One in Tilburg, a cooperative in a Southern city of the Netherlands using an expert system, and one in Groningen, a cooperative in a Northern city not using an expert system. Some other relevant information about the care process was collected additionally. Data about call duration was compared using an independent sample t-test. Data about call decisions was compared using Chi Square. The mean call time in the cooperative using the TAS expert system is 4.6 minutes, in the cooperative not using the expert system 3.9 minutes. A significant difference of 0.7 minutes (0.4 - 1.0, 95% CI) minutes. In the cooperative with an expert system a larger percentage of patients is handled by the assistant, patients are less often referred to a telephone consultation with the GP and are less likely to be offered a visit by the GP.A quick interpretation of the impact of the difference in triage decisions, show that these may be large enough to support the hypothesis that longer call duration is compensated for by less contacts with the GP (by telephone or face-to-face). There is no proof, however, that these differences are caused by the use of the triage system. The larger amount of calls handled by the assistant may be partly caused by the fact that the assistants in the cooperative with an expert system more often consult the GP during triage. And it is not likely that the larger amount of home visits in Groningen can be attributed to the absence of an expert system. The expert system only offers advice whether a GP should be seen, not in which way (by consultation in the office or by home visit). The differences in call times between a cooperative using an expert system and a cooperative not using an expert system are small; 0.4 - 1.0 min. Differences in triage decisions were found, but it is not proven that these can be contributed to the use of an expert system.

Call-duration and triage decisions in out of hours cooperatives with and without the use of an expert system

PubMed Central

Ong, Rob SG; Post, Johan; van Rooij, Harry; de Haan, Jan

2008-01-01

Background Cooperatives delivering out of hours care in the Netherlands are hesitant about the use of expert systems during triage. Apart from the extra costs, cooperatives are not sure that quality of triage is sufficiently enhanced by these systems and believe that call duration will be prolonged drastically. No figures about the influence of the use of an expert system during triage on call duration and triage decisions in out of hours care in the Netherlands are available. Methods Electronically registered data concerning call duration and triage decisions were collected in two cooperatives. One in Tilburg, a cooperative in a Southern city of the Netherlands using an expert system, and one in Groningen, a cooperative in a Northern city not using an expert system. Some other relevant information about the care process was collected additionally. Data about call duration was compared using an independent sample t-test. Data about call decisions was compared using Chi Square. Results The mean call time in the cooperative using the TAS expert system is 4.6 minutes, in the cooperative not using the expert system 3.9 minutes. A significant difference of 0.7 minutes (0.4 – 1.0, 95% CI) minutes. In the cooperative with an expert system a larger percentage of patients is handled by the assistant, patients are less often referred to a telephone consultation with the GP and are less likely to be offered a visit by the GP. A quick interpretation of the impact of the difference in triage decisions, show that these may be large enough to support the hypothesis that longer call duration is compensated for by less contacts with the GP (by telephone or face-to-face). There is no proof, however, that these differences are caused by the use of the triage system. The larger amount of calls handled by the assistant may be partly caused by the fact that the assistants in the cooperative with an expert system more often consult the GP during triage. And it is not likely that the larger amount of home visits in Groningen can be attributed to the absence of an expert system. The expert system only offers advice whether a GP should be seen, not in which way (by consultation in the office or by home visit). Conclusion The differences in call times between a cooperative using an expert system and a cooperative not using an expert system are small; 0.4 – 1.0 min. Differences in triage decisions were found, but it is not proven that these can be contributed to the use of an expert system. PMID:18271970

Take-the-best in expert-novice decision strategies for residential burglary.

PubMed

Garcia-Retamero, Rocio; Dhami, Mandeep K

2009-02-01

We examined the decision strategies and cue use of experts and novices in a consequential domain: crime. Three participant groups decided which of two residential properties was more likely to be burgled, on the basis of eight cues such as location of the property. The two expert groups were experienced burglars and police officers, and the novice group was composed of graduate students. We found that experts' choices were best predicted by a lexicographic heuristic strategy called take-the-best that implies noncompensatory information processing, whereas novices' choices were best predicted by a weighted additive linear strategy that implies compensatory processing. The two expert groups, however, differed in the cues they considered important in making their choices, and the police officers were actually more similar to novices in this regard. These findings extend the literature on judgment, decision making, and expertise, and have implications for criminal justice policy.

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Comparison of display enhancement with intelligent decision-aiding

NASA Technical Reports Server (NTRS)

Kirlik, Alex; Markert, Wendy J.; Kossack, Merrick

1992-01-01

Currently, two main approaches exist for improving the human-machine interface component of a system in order to improve overall system performance, display enhancement and intelligent decision aiding. Each of these two approaches has its own set of advantages and disadvantages, as well as introduce its own set of additional performance problems. These characteristics should help identify which types of problem situations and domains are better aided by which type of strategy. The characteristic issues are described of these two decision aiding strategies. Then differences in expert and novice decision making are described in order to help determine whether a particular strategy may be better for a particular type of user. Finally, research is outlined to compare and contrast the two technologies, as well as to examine the interaction effects introduced by the different skill levels and the different methods for training operators.

Mining data from hemodynamic simulations for generating prediction and explanation models.

PubMed

Bosnić, Zoran; Vračar, Petar; Radović, Milos D; Devedžić, Goran; Filipović, Nenad D; Kononenko, Igor

2012-03-01

One of the most common causes of human death is stroke, which can be caused by carotid bifurcation stenosis. In our work, we aim at proposing a prototype of a medical expert system that could significantly aid medical experts to detect hemodynamic abnormalities (increased artery wall shear stress). Based on the acquired simulated data, we apply several methodologies for1) predicting magnitudes and locations of maximum wall shear stress in the artery, 2) estimating reliability of computed predictions, and 3) providing user-friendly explanation of the model's decision. The obtained results indicate that the evaluated methodologies can provide a useful tool for the given problem domain. © 2012 IEEE

The integration of quantitative information with an intelligent decision support system for residential energy retrofits

NASA Astrophysics Data System (ADS)

Mo, Yunjeong

The purpose of this research is to support the development of an intelligent Decision Support System (DSS) by integrating quantitative information with expert knowledge in order to facilitate effective retrofit decision-making. To achieve this goal, the Energy Retrofit Decision Process Framework is analyzed. Expert system shell software, a retrofit measure cost database, and energy simulation software are needed for developing the DSS; Exsys Corvid, the NREM database and BEopt were chosen for implementing an integration model. This integration model demonstrates the holistic function of a residential energy retrofit system for existing homes, by providing a prioritized list of retrofit measures with cost information, energy simulation and expert advice. The users, such as homeowners and energy auditors, can acquire all of the necessary retrofit information from this unified system without having to explore several separate systems. The integration model plays the role of a prototype for the finalized intelligent decision support system. It implements all of the necessary functions for the finalized DSS, including integration of the database, energy simulation and expert knowledge.

Hybrid expert system for decision supporting in the medical area: complexity and cognitive computing.

PubMed

Brasil, L M; de Azevedo, F M; Barreto, J M

2001-09-01

This paper proposes a hybrid expert system (HES) to minimise some complexity problems pervasive to the artificial intelligence such as: the knowledge elicitation process, known as the bottleneck of expert systems; the model choice for knowledge representation to code human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach; the difficulty to obtain the explanation on how the network arrived to a conclusion. Two algorithms applied to developing of HES are also suggested. One of them is used to train the fuzzy neural network and the other to obtain explanations on how the fuzzy neural network attained a conclusion. To overcome these difficulties the cognitive computing was integrated to the developed system. A case study is presented (e.g. epileptic crisis) with the problem definition and simulations. Results are also discussed.

The Success of Linear Bootstrapping Models: Decision Domain-, Expertise-, and Criterion-Specific Meta-Analysis

PubMed Central

Kaufmann, Esther; Wittmann, Werner W.

2016-01-01

The success of bootstrapping or replacing a human judge with a model (e.g., an equation) has been demonstrated in Paul Meehl’s (1954) seminal work and bolstered by the results of several meta-analyses. To date, however, analyses considering different types of meta-analyses as well as the potential dependence of bootstrapping success on the decision domain, the level of expertise of the human judge, and the criterion for what constitutes an accurate decision have been missing from the literature. In this study, we addressed these research gaps by conducting a meta-analysis of lens model studies. We compared the results of a traditional (bare-bones) meta-analysis with findings of a meta-analysis of the success of bootstrap models corrected for various methodological artifacts. In line with previous studies, we found that bootstrapping was more successful than human judgment. Furthermore, bootstrapping was more successful in studies with an objective decision criterion than in studies with subjective or test score criteria. We did not find clear evidence that the success of bootstrapping depended on the decision domain (e.g., education or medicine) or on the judge’s level of expertise (novice or expert). Correction of methodological artifacts increased the estimated success of bootstrapping, suggesting that previous analyses without artifact correction (i.e., traditional meta-analyses) may have underestimated the value of bootstrapping models. PMID:27327085

Development of an expert system for assessing trumpeter swan breeding habitat in the Northern Rocky Mountains.

USGS Publications Warehouse

Sojda, Richard S.; Cornely, John E.; Howe, Adele E.

2002-01-01

A decision support system for the management of the Rocky Mountain Population of Trumpeter Swans (Cygnus buccinators) is being developed. As part of this, three expert systems are also in development: one for assessing the quality of Trumpeter Swan breeding habitat; one for making water level recommendations in montane, palustrine wetlands; and one for assessing the contribution a particular site can make towards meeting objectives from as flyway perspective. The focus of this paper is the development of the breeding habitat expert system, which currently consists of 157 rules. Out purpose is to provide decision support for issues that appear to be beyond the capability of a single persons to conceptualize and solve. We propose that by involving multiple experts in the development and use of the systems, management will be significantly improved. The knowledge base for the expert system has been developed using standard knowledge engineering techniques with a small team of ecological experts. Knowledge was then coded using production rules organized in decision trees using a commercial expert system development shell. The final system has been deployed on the world wide web.

Developing collaborative classifiers using an expert-based model

USGS Publications Warehouse

Mountrakis, G.; Watts, R.; Luo, L.; Wang, Jingyuan

2009-01-01

This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Assessing the teaching of procedural skills: can cognitive task analysis add to our traditional teaching methods?

PubMed

Sullivan, Maura E; Ortega, Adrian; Wasserberg, Nir; Kaufman, Howard; Nyquist, Julie; Clark, Richard

2008-01-01

The purpose of this study was to determine if a cognitive task analysis (CTA) could capture steps and decision points that were not articulated during traditional teaching of a colonoscopy. Three expert colorectal surgeons were videotaped performing a colonoscopy. After the videotapes were transcribed, the experts participated in a CTA. A 26-step procedural checklist and a 16-step cognitive demands table was created by using information obtained in the CTA. The videotape transcriptions were transposed onto the procedural checklist and cognitive demands table to identify steps and decision points that were omitted during traditional teaching. Surgeon A described 50% of "how-to" steps and 43% of decision points. Surgeon B described 30% of steps and 25% of decisions. Surgeon C described 26% of steps and 38% of cognitive decisions. By using CTA, we were able to identify relevant steps and decision points that were omitted during traditional teaching by all 3 experts.

Expert Consensus for Discharge Referral Decisions Using Online Delphi

PubMed Central

Bowles, Kathy H.; Holmes, John H.; Naylor, Mary D.; Liberatore, Matthew; Nydick, Robert

2003-01-01

This paper describes the results of using a modified Delphi approach designed to achieve consensus from eight discharge planning experts regarding the decision to refer hospitalized older adults for post-discharge follow-up. Experts reviewed 150 cases using an online website designed to facilitate their interaction and efforts to reach agreement on the need for a referral for post-discharge care and the appropriate site for such care. In contrast to an average of eight weeks to complete just 50 cases using the traditional mail method, the first online Delphi round for 150 cases were completed in six weeks. Data provided by experts suggest that online Delphi is a time efficient and acceptable methodology for reaching group consensus. Other benefits include instant access to Delphi decision results, live knowledge of the time requirements and progress of each expert, and cost savings in postage, paper, copying, and storage of paper documents. This online Delphi methodology is highly recommended. PMID:14728143

Developing a systematic approach to safer medication use during pregnancy: summary of a Centers for Disease Control and Prevention--convened meeting.

PubMed

Broussard, Cheryl S; Frey, Meghan T; Hernandez-Diaz, Sonia; Greene, Michael F; Chambers, Christina D; Sahin, Leyla; Collins Sharp, Beth A; Honein, Margaret A

2014-09-01

To address information gaps that limit informed clinical decisions on medication use in pregnancy, the Centers for Disease Control and Prevention (CDC) solicited expert input on a draft prototype outlining a systematic approach to evaluating the quality and strength of existing evidence for associated risks. The draft prototype outlined a process for the systematic review of available evidence and deliberations by a panel of experts to inform clinical decision making for managing health conditions in pregnancy. At an expert meeting convened by the CDC in January 2013, participants divided into working groups discussed decision points within the prototype. This report summarizes their discussions of best practices for formulating an expert review process, developing evidence summaries and treatment guidance, and disseminating information. There is clear recognition of current knowledge gaps and a strong collaboration of federal partners, academic experts, and professional organizations willing to work together toward safer medication use during pregnancy. Published by Elsevier Inc.

Developing a systematic approach to safer medication use during pregnancy: summary of a Centers for Disease Control and Prevention—convened meeting

PubMed Central

Broussard, Cheryl S.; Frey, Meghan T.; Hernandez-Diaz, Sonia; Greene, Michael F.; Chambers, Christina D.; Sahin, Leyla; Collins Sharp, Beth A.; Honein, Margaret A.

2015-01-01

To address information gaps that limit informed clinical decisions on medication use in pregnancy, the Centers for Disease Control and Prevention (CDC) solicited expert input on a draft prototype outlining a systematic approach to evaluating the quality and strength of existing evidence for associated risks. The draft prototype outlined a process for the systematic review of available evidence and deliberations by a panel of experts to inform clinical decision making for managing health conditions in pregnancy. At an expert meeting convened by the CDC in January 2013, participants divided into working groups discussed decision points within the prototype. This report summarizes their discussions of best practices for formulating an expert review process, developing evidence summaries and treatment guidance, and disseminating information. There is clear recognition of current knowledge gaps and a strong collaboration of federal partners, academic experts, and professional organizations willing to work together toward safer medication use during pregnancy. PMID:24881821

Expertise transfer for expert system design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boose, J.H.

This book is about the Expertise Transfer System-a computer program which interviews experts and helps them build expert systems, i.e. computer programs that use knowledge from experts to make decisions and judgements under conditions of uncertainty. The techniques are useful to anyone who uses decision-making information based on the expertise of others. The methods can also be applied to personal decision-making. The interviewing methodology is borrowed from a branch of psychology called Personal Construct Theory. It is not necessary to use a computer to take advantage of the techniques from Personal Construction Theory; the fundamental procedures used by the Expertisemore » Transfer System can be performed using paper and pencil. It is not necessary that the reader understand very much about computers to understand the ideas in this book. The few relevant concepts from computer science and expert systems that are needed are explained in a straightforward manner. Ideas from Personal Construct Psychology are also introduced as needed.« less

Knowledge Requirements and Management in Expert Decision Support Systems for (Military) Situation Assessment

DTIC Science & Technology

1983-08-01

constitutes a fundamental problem in many decision making processes. In business management we face this problem when determining the status of an...Tehiical Report 576 ( 1 ) 4 KNOWLEDGE REQUIREMENTS AND MANAGEMENT IN EXPERT DECISION SUPPORT SYSTEMS FOR (MILITARY) SITUATION ASSESSMENT MOOM sen...accomplished under contract for the Department of the Army The Israel Institute of Business Research Technical review by Robert H. Sasmor Joseph M

Human Space Flight

NASA Technical Reports Server (NTRS)

Woolford, Barbara

2006-01-01

The performance of complex tasks on the International Space Station (ISS) requires significant preflight crew training commitments and frequent skill and knowledge refreshment. This report documents a recently developed just-in-time training methodology, which integrates preflight hardware familiarization and procedure training with an on-orbit CD-ROM-based skill enhancement. This just-in-time concept was used to support real-time remote expert guidance to complete medical examinations using the ISS Human Research Facility (HRF). An American md Russian ISS crewmember received 2-hours of hands on ultrasound training 8 months prior to the on-orbit ultrasound exam. A CD-ROM-based Onboard Proficiency Enhancement (OPE) interactive multimedia program consisting of memory enhancing tutorials, and skill testing exercises, was completed by the crewmember six days prior to the on-orbit ultrasound exam. The crewmember was then remotely guided through a thoracic, vascular, and echocardiographic examination by ultrasound imaging experts. Results of the CD ROM based OPE session were used to modify the instructions during a complete 35 minute real-time thoracic, cardiac, and carotid/jugular ultrasound study. Following commands from the ground-based expert, the crewmember acquired all target views and images without difficulty. The anatomical content and fidelity of ultrasound video were excellent and adequate for clinical decision-making. Complex ultrasound experiments with expert guidance were performed with high accuracy following limited pre-flight training and CD-ROM-based in-flight review, despite a 2-second communication latency.

Different contributions of internal reviewers and external experts to labelling decisions on therapeutic indications in new drug reviews in Japan.

PubMed

Yokota, M; Kusama, M; Matsuki, N; Ono, S

2013-12-01

External experts play an important role in shaping regulatory decisions in the new drug review process in the United States, Europe and Japan. No rigorous study has been performed addressing how and to what extent external experts, in contrast to internal reviewers in the agency, influence the regulatory decisions during new drug reviews. We examined their contributions in Japanese regulatory reviews in contrast to the internal reviewers, focusing on the labelling decision on therapeutic indications. With the data set of 219 new molecular entities (NMEs) approved in Japan from 2000 to 2009, we observed how proposed indications in labelling were modified in a stepwise manner during the review process and conducted multinomial logistic analysis to examine the possible mechanism behind. We found that interim assessment of indications by the internal reviewers was modified substantially by the influence of the external experts in about 20% of the 219 NMEs. Our analysis suggested that internal reviewers provided their opinion mainly based on strict review discipline, whereas external experts added flexibility and reality to their reviews. Our analysis revealed different evaluations between internal reviewers and external experts during regulatory discussions in new drug reviews and how the external panel contributes to changing internal decisions. This study provides a new and quantitative approach to better label setting by emphasizing the contributions of each stakeholder in new drug reviews, which would improve the efficiency, quality and transparency of new drug reviews to enhance public health. © 2013 John Wiley & Sons Ltd.

Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

PubMed

Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

2015-11-30

Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients.

Human Factors Report on Information Management Requirements for Next- Generation Manned Bombers

DTIC Science & Technology

1987-12-01

34 James , W. G. (1984). Al applications to military pilot decision aiding -- A perspective • transition. In Third Aerospace Behavioral Engineering Techno.ogy...8217- - . . . Basden , A. (1983). On the application of expert systems. International Journal of Man-Machine Studies, 19, 461-477. Ben-Bassat, M. and Freedy, A...augmentation system design by defining, developing, and applying appropriate design techniques for a variety of airborne platforms. James , W. G

A comparison of two methods for expert elicitation in health technology assessments.

PubMed

Grigore, Bogdan; Peters, Jaime; Hyde, Christopher; Stein, Ken

2016-07-26

When data needed to inform parameters in decision models are lacking, formal elicitation of expert judgement can be used to characterise parameter uncertainty. Although numerous methods for eliciting expert opinion as probability distributions exist, there is little research to suggest whether one method is more useful than any other method. This study had three objectives: (i) to obtain subjective probability distributions characterising parameter uncertainty in the context of a health technology assessment; (ii) to compare two elicitation methods by eliciting the same parameters in different ways; (iii) to collect subjective preferences of the experts for the different elicitation methods used. Twenty-seven clinical experts were invited to participate in an elicitation exercise to inform a published model-based cost-effectiveness analysis of alternative treatments for prostate cancer. Participants were individually asked to express their judgements as probability distributions using two different methods - the histogram and hybrid elicitation methods - presented in a random order. Individual distributions were mathematically aggregated across experts with and without weighting. The resulting combined distributions were used in the probabilistic analysis of the decision model and mean incremental cost-effectiveness ratios and the expected values of perfect information (EVPI) were calculated for each method, and compared with the original cost-effectiveness analysis. Scores on the ease of use of the two methods and the extent to which the probability distributions obtained from each method accurately reflected the expert's opinion were also recorded. Six experts completed the task. Mean ICERs from the probabilistic analysis ranged between £162,600-£175,500 per quality-adjusted life year (QALY) depending on the elicitation and weighting methods used. Compared to having no information, use of expert opinion decreased decision uncertainty: the EVPI value at the £30,000 per QALY threshold decreased by 74-86 % from the original cost-effectiveness analysis. Experts indicated that the histogram method was easier to use, but attributed a perception of more accuracy to the hybrid method. Inclusion of expert elicitation can decrease decision uncertainty. Here, choice of method did not affect the overall cost-effectiveness conclusions, but researchers intending to use expert elicitation need to be aware of the impact different methods could have.

Decision making in prioritization of required operational capabilities

NASA Astrophysics Data System (ADS)

Andreeva, P.; Karev, M.; Kovacheva, Ts.

2015-10-01

The paper describes an expert heuristic approach to prioritization of required operational capabilities in the field of defense. Based on expert assessment and by application of the method of Analytical Hierarchical Process, a methodology for their prioritization has been developed. It has been applied to practical simulation decision making games.

Expert systems in civil engineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostem, C.N.; Maher, M.L.

1986-01-01

This book presents the papers given at a symposium on expert systems in civil engineering. Topics considered at the symposium included problem solving using expert system techniques, construction schedule analysis, decision making and risk analysis, seismic risk analysis systems, an expert system for inactive hazardous waste site characterization, an expert system for site selection, knowledge engineering, and knowledge-based expert systems in seismic analysis.

Identifying psychophysiological indices of expert vs. novice performance in deadly force judgment and decision making

PubMed Central

Johnson, Robin R.; Stone, Bradly T.; Miranda, Carrie M.; Vila, Bryan; James, Lois; James, Stephen M.; Rubio, Roberto F.; Berka, Chris

2014-01-01

Objective: To demonstrate that psychophysiology may have applications for objective assessment of expertise development in deadly force judgment and decision making (DFJDM). Background: Modern training techniques focus on improving decision-making skills with participative assessment between trainees and subject matter experts primarily through subjective observation. Objective metrics need to be developed. The current proof of concept study explored the potential for psychophysiological metrics in deadly force judgment contexts. Method: Twenty-four participants (novice, expert) were recruited. All wore a wireless Electroencephalography (EEG) device to collect psychophysiological data during high-fidelity simulated deadly force judgment and decision-making simulations using a modified Glock firearm. Participants were exposed to 27 video scenarios, one-third of which would have justified use of deadly force. Pass/fail was determined by whether the participant used deadly force appropriately. Results: Experts had a significantly higher pass rate compared to novices (p < 0.05). Multiple metrics were shown to distinguish novices from experts. Hierarchical regression analyses indicate that psychophysiological variables are able to explain 72% of the variability in expert performance, but only 37% in novices. Discriminant function analysis (DFA) using psychophysiological metrics was able to discern between experts and novices with 72.6% accuracy. Conclusion: While limited due to small sample size, the results suggest that psychophysiology may be developed for use as an objective measure of expertise in DFDJM. Specifically, discriminant function measures may have the potential to objectively identify expert skill acquisition. Application: Psychophysiological metrics may create a performance model with the potential to optimize simulator-based DFJDM training. These performance models could be used for trainee feedback, and/or by the instructor to assess performance objectively. PMID:25100966

A hybrid fuzzy logic/constraint satisfaction problem approach to automatic decision making in simulation game models.

PubMed

Braathen, Sverre; Sendstad, Ole Jakob

2004-08-01

Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.

Expert cognition in the production sequence of Acheulian cleavers at Gesher Benot Ya'aqov, Israel: A lithic and cognitive analysis

PubMed Central

Wynn, Thomas; Goren-Inbar, Naama

2017-01-01

Stone cleavers are one of the most distinctive components of the Acheulian toolkit. These tools were produced as part of a long and complex reduction sequence and they provide indications for planning and remarkable knapping skill. These aspects hold implications regarding the cognitive complexity and abilities of their makers and users. In this study we have analyzed a cleaver assemblage originating from the Acheulian site of Gesher Benot Ya‘aqov, Israel, to provide a reconstruction of the chaîne opératoire which structured their production. This reduction sequence was taken as the basis for a cognitive analysis which allowed us to draw conclusion regarding numerous behavioral and cognitive aspects of the GBY hominins. The results indicate that the cleavers production incorporated a highly specific sequence of decisions and actions which resulted in three distinct modes of cleavers modification. Furthermore, the decision to produce a cleaver must have been taken very early in the sequence, thus differentiating its production from that of handaxes. The substantial predetermination and the specific reduction sequence provide evidence that the Gesher Benot Ya‘aqov hominins had a number of cognitive categories such as a general ‘tool concept’ and a more specific ‘cleaver concept’, setting them apart from earlier tool-producing hominins and extant tool-using non-human primates. Furthermore, it appears that the Gesher Benot Ya‘aqov lithic technology was governed by expert cognition, which is the kind of thinking typical of modern human experts in their various domains. Thus, the results provide direct indications that important components of modern cognition have been well established in the minds of the Gesher Benot Ya‘aqov hominins. PMID:29145489

Expert cognition in the production sequence of Acheulian cleavers at Gesher Benot Ya'aqov, Israel: A lithic and cognitive analysis.

PubMed

Herzlinger, Gadi; Wynn, Thomas; Goren-Inbar, Naama

2017-01-01

Stone cleavers are one of the most distinctive components of the Acheulian toolkit. These tools were produced as part of a long and complex reduction sequence and they provide indications for planning and remarkable knapping skill. These aspects hold implications regarding the cognitive complexity and abilities of their makers and users. In this study we have analyzed a cleaver assemblage originating from the Acheulian site of Gesher Benot Ya'aqov, Israel, to provide a reconstruction of the chaîne opératoire which structured their production. This reduction sequence was taken as the basis for a cognitive analysis which allowed us to draw conclusion regarding numerous behavioral and cognitive aspects of the GBY hominins. The results indicate that the cleavers production incorporated a highly specific sequence of decisions and actions which resulted in three distinct modes of cleavers modification. Furthermore, the decision to produce a cleaver must have been taken very early in the sequence, thus differentiating its production from that of handaxes. The substantial predetermination and the specific reduction sequence provide evidence that the Gesher Benot Ya'aqov hominins had a number of cognitive categories such as a general 'tool concept' and a more specific 'cleaver concept', setting them apart from earlier tool-producing hominins and extant tool-using non-human primates. Furthermore, it appears that the Gesher Benot Ya'aqov lithic technology was governed by expert cognition, which is the kind of thinking typical of modern human experts in their various domains. Thus, the results provide direct indications that important components of modern cognition have been well established in the minds of the Gesher Benot Ya'aqov hominins.

Toward fisheries sustainability in North America: Issues, challenges, and strategies for action

USGS Publications Warehouse

MacDonald, D.D.; Knudsen, E.E.

2004-01-01

Many fisheries in North America are severely depleted and trending downwards. In an effort to find ways of reversing this disturbing situation, the American Fisheries Society and the Sustainable Fisheries Foundation invited leading experts in fisheries science and aquatic resource management to share their thoughts and insights in this book. These experts were asked to identify the factors that are currently impairing our ability to effectively manage fisheries resources and propose creative solutions for addressing the most challenging issues affecting fisheries sustainability. Based on the information that was provided by the experts (i.e., as presented in the earlier chapters of this book), it is apparent that a wide range of human activities are adversely affecting our shared fisheries resources and the aquatic habitats upon which they depend. The most challenging problems stem from causes that are largely beyond the scope of traditional fisheries management (e.g., human population growth, resource consumption patterns, global climate change, broad land-use patterns). It is also apparent that resolution of these challenges will require a new approach to fisheries management - one that effectively integrates economic, social, and environmental interests into a decision-making framework that supports fisheries sustainability. The key strategies for supporting such a transition toward a more holistic and comprehensive approach to managing the human activities that influence fisheries and aquatic resources are summarized in this chapter. ?? 2004 by the American Fisheries Society.

Economics of human trafficking.

PubMed

Wheaton, Elizabeth M; Schauer, Edward J; Galli, Thomas V

2010-01-01

Because freedom of choice and economic gain are at the heart of productivity, human trafficking impedes national and international economic growth. Within the next 10 years, crime experts expect human trafficking to surpass drug and arms trafficking in its incidence, cost to human well-being, and profitability to criminals (Schauer and Wheaton, 2006: 164-165). The loss of agency from human trafficking as well as from modern slavery is the result of human vulnerability (Bales, 2000: 15). As people become vulnerable to exploitation and businesses continually seek the lowest-cost labour sources, trafficking human beings generates profit and a market for human trafficking is created. This paper presents an economic model of human trafficking that encompasses all known economic factors that affect human trafficking both across and within national borders. We envision human trafficking as a monopolistically competitive industry in which traffickers act as intermediaries between vulnerable individuals and employers by supplying differentiated products to employers. In the human trafficking market, the consumers are employers of trafficked labour and the products are human beings. Using a rational-choice framework of human trafficking we explain the social situations that shape relocation and working decisions of vulnerable populations leading to human trafficking, the impetus for being a trafficker, and the decisions by employers of trafficked individuals. The goal of this paper is to provide a common ground upon which policymakers and researchers can collaborate to decrease the incidence of trafficking in humans.

A Decision-Support System for Sustainable Water Distribution System Planning.

PubMed

Freund, Alina; Aydin, Nazli Yonca; Zeckzer, Dirk; Hagen, Hans

2017-01-01

An interactive decision-support system (DSS) can help experts prepare water resource management plans for decision makers and stakeholders. The design of the proposed prototype incorporates visualization techniques such as circle views, grid layout, small multiple maps, and node simplification to improve the data readability of water distribution systems. A case study with three urban water management and sanitary engineering experts revealed that the proposed DSS is satisfactory, efficient, and effective.

Relying on experts as we reason together.

PubMed

Richardson, Henry S

2012-06-01

In various contexts, it is thought to be important that we reason together. For instance, an attractive conception of democracy requires that citizens reach lawmaking decisions by reasoning with one another. Reasoning requires that reasoners survey the considerations that they take to be reasons, proceed by a coherent train of thought, and reach conclusions freely. De facto reliance on experts threatens the possibility of collective reasoning by making some reasons collectively unsurveyable, raising questions about the coherence of the resulting train of thought. De jure reliance on experts threatens the possibility of collective reasoning by seeming to make some conclusions irreversible. The paper argues that collective reasoning that relies on experts would nonetheless be possible if the unsurveyable reasons "mesh," if the expert considerations are at least in principle publicly recoverable, and if de jure authority of expert decision is always subject to appeal.

Science-based HRA: experimental comparison of operator performance to IDAC (Information-Decision-Action Crew) simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shirley, Rachel; Smidts, Carol; Boring, Ronald

Information-Decision-Action Crew (IDAC) operator model simulations of a Steam Generator Tube Rupture are compared to student operator performance in studies conducted in the Ohio State University’s Nuclear Power Plant Simulator Facility. This study is presented as a prototype for conducting simulator studies to validate key aspects of Human Reliability Analysis (HRA) methods. Seven student operator crews are compared to simulation results for crews designed to demonstrate three different decision-making strategies. The IDAC model used in the simulations is modified slightly to capture novice behavior rather that expert operators. Operator actions and scenario pacing are compared. A preliminary review of availablemore » performance shaping factors (PSFs) is presented. After the scenario in the NPP Simulator Facility, student operators review a video of the scenario and evaluate six PSFs at pre-determined points in the scenario. This provides a dynamic record of the PSFs experienced by the OSU student operators. In this preliminary analysis, Time Constraint Load (TCL) calculated in the IDAC simulations is compared to TCL reported by student operators. We identify potential modifications to the IDAC model to develop an “IDAC Student Operator Model.” This analysis provides insights into how similar experiments could be conducted using expert operators to improve the fidelity of IDAC simulations.« less

The potential for intelligent decision support systems to improve the quality and consistency of medication reviews.

PubMed

Bindoff, I; Stafford, A; Peterson, G; Kang, B H; Tenni, P

2012-08-01

Drug-related problems (DRPs) are of serious concern worldwide, particularly for the elderly who often take many medications simultaneously. Medication reviews have been demonstrated to improve medication usage, leading to reductions in DRPs and potential savings in healthcare costs. However, medication reviews are not always of a consistently high standard, and there is often room for improvement in the quality of their findings. Our aim was to produce computerized intelligent decision support software that can improve the consistency and quality of medication review reports, by helping to ensure that DRPs relevant to a patient are overlooked less frequently. A system that largely achieved this goal was previously published, but refinements have been made. This paper examines the results of both the earlier and newer systems. Two prototype multiple-classification ripple-down rules medication review systems were built, the second being a refinement of the first. Each of the systems was trained incrementally using a human medication review expert. The resultant knowledge bases were analysed and compared, showing factors such as accuracy, time taken to train, and potential errors avoided. The two systems performed well, achieving accuracies of approximately 80% and 90%, after being trained on only a small number of cases (126 and 244 cases, respectively). Through analysis of the available data, it was estimated that without the system intervening, the expert training the first prototype would have missed approximately 36% of potentially relevant DRPs, and the second 43%. However, the system appeared to prevent the majority of these potential expert errors by correctly identifying the DRPs for them, leaving only an estimated 8% error rate for the first expert and 4% for the second. These intelligent decision support systems have shown a clear potential to substantially improve the quality and consistency of medication reviews, which should in turn translate into improved medication usage if they were implemented into routine use. © 2011 Blackwell Publishing Ltd.

Visual skills involved in decision making by expert referees.

PubMed

Ghasemi, Abdollah; Momeni, Maryam; Jafarzadehpur, Ebrahim; Rezaee, Meysam; Taheri, Hamid

2011-02-01

Previous studies have compared visual skills of expert and novice athletes; referees' performance has not been addressed. Visual skills of two groups of expert referees, successful and unsuccessful in decision making, were compared. Using video clips of soccer matches to assess decision-making success of 41 national and international referees from 31 to 42 years of age, 10 top referees were selected as the Successful group and 10 as the Unsuccessful group. Visual tests included visual memory, visual reaction time, peripheral vision, recognition speed, saccadic eye movement, and facility of accommodation. The Successful group had better visual skills than the Unsuccessful group. Such visual skills enhance soccer referees' performance and may be recommended for young referees.

Electronic collaboration: Some effects of telecommunication media and machine intelligence on team performance

NASA Technical Reports Server (NTRS)

Wellens, A. Rodney

1991-01-01

Both NASA and DoD have had a long standing interest in teamwork, distributed decision making, and automation. While research on these topics has been pursued independently, it is becoming increasingly clear that the integration of social, cognitive, and human factors engineering principles will be necessary to meet the challenges of highly sophisticated scientific and military programs of the future. Images of human/intelligent-machine electronic collaboration were drawn from NASA and Air Force reports as well as from other sources. Here, areas of common concern are highlighted. A description of the author's research program testing a 'psychological distancing' model of electronic media effects and human/expert system collaboration is given.

Functional specifications for a radioactive waste decision support system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Westrom, G.B.; Kurrasch, E.R.; Carlton, R.E.

1989-09-01

It is generally recognized that decisions relative to the treatment, handling, transportation and disposal of low-level wastes produced in nuclear power plants involve a complex array of many inter-related elements or considerations. Complex decision processes can be aided through the use of computer-based expert systems which are based on the knowledge of experts and the inferencing of that knowledge to provide advice to an end-user. To determine the feasibility of developing and applying an expert system in nuclear plant low level waste operations, a Functional Specification for a Radwaste Decision Support System (RDSS) was developed. All areas of radwaste management,more » from the point of waste generation to the disposition of the waste in the final disposal location were considered for inclusion within the scope of the RDSS. 27 figs., 8 tabs.« less

World Health Organization Estimates of the Relative Contributions of Food to the Burden of Disease Due to Selected Foodborne Hazards: A Structured Expert Elicitation

PubMed Central

Hald, Tine; Aspinall, Willy; Devleesschauwer, Brecht; Cooke, Roger; Corrigan, Tim; Havelaar, Arie H.; Gibb, Herman J.; Torgerson, Paul R.; Kirk, Martyn D.; Angulo, Fred J.; Lake, Robin J.; Speybroeck, Niko; Hoffmann, Sandra

2016-01-01

Background The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization (WHO) to estimate the global burden of foodborne diseases (FBDs). This estimation is complicated because most of the hazards causing FBD are not transmitted solely by food; most have several potential exposure routes consisting of transmission from animals, by humans, and via environmental routes including water. This paper describes an expert elicitation study conducted by the FERG Source Attribution Task Force to estimate the relative contribution of food to the global burden of diseases commonly transmitted through the consumption of food. Methods and Findings We applied structured expert judgment using Cooke’s Classical Model to obtain estimates for 14 subregions for the relative contributions of different transmission pathways for eleven diarrheal diseases, seven other infectious diseases and one chemical (lead). Experts were identified through international networks followed by social network sampling. Final selection of experts was based on their experience including international working experience. Enrolled experts were scored on their ability to judge uncertainty accurately and informatively using a series of subject-matter specific ‘seed’ questions whose answers are unknown to the experts at the time they are interviewed. Trained facilitators elicited the 5th, and 50th and 95th percentile responses to seed questions through telephone interviews. Cooke’s Classical Model uses responses to the seed questions to weigh and aggregate expert responses. After this interview, the experts were asked to provide 5th, 50th, and 95th percentile estimates for the ‘target’ questions regarding disease transmission routes. A total of 72 experts were enrolled in the study. Ten panels were global, meaning that the experts should provide estimates for all 14 subregions, whereas the nine panels were subregional, with experts providing estimates for one or more subregions, depending on their experience in the region. The size of the 19 hazard-specific panels ranged from 6 to 15 persons with several experts serving on more than one panel. Pathogens with animal reservoirs (e.g. non-typhoidal Salmonella spp. and Toxoplasma gondii) were in general assessed by the experts to have a higher proportion of illnesses attributable to food than pathogens with mainly a human reservoir, where human-to-human transmission (e.g. Shigella spp. and Norovirus) or waterborne transmission (e.g. Salmonella Typhi and Vibrio cholerae) were judged to dominate. For many pathogens, the foodborne route was assessed relatively more important in developed subregions than in developing subregions. The main exposure routes for lead varied across subregions, with the foodborne route being assessed most important only in two subregions of the European region. Conclusions For the first time, we present worldwide estimates of the proportion of specific diseases attributable to food and other major transmission routes. These findings are essential for global burden of FBD estimates. While gaps exist, we believe the estimates presented here are the best current source of guidance to support decision makers when allocating resources for control and intervention, and for future research initiatives. PMID:26784029

World Health Organization Estimates of the Relative Contributions of Food to the Burden of Disease Due to Selected Foodborne Hazards: A Structured Expert Elicitation.

PubMed

Hald, Tine; Aspinall, Willy; Devleesschauwer, Brecht; Cooke, Roger; Corrigan, Tim; Havelaar, Arie H; Gibb, Herman J; Torgerson, Paul R; Kirk, Martyn D; Angulo, Fred J; Lake, Robin J; Speybroeck, Niko; Hoffmann, Sandra

2016-01-01

The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization (WHO) to estimate the global burden of foodborne diseases (FBDs). This estimation is complicated because most of the hazards causing FBD are not transmitted solely by food; most have several potential exposure routes consisting of transmission from animals, by humans, and via environmental routes including water. This paper describes an expert elicitation study conducted by the FERG Source Attribution Task Force to estimate the relative contribution of food to the global burden of diseases commonly transmitted through the consumption of food. We applied structured expert judgment using Cooke's Classical Model to obtain estimates for 14 subregions for the relative contributions of different transmission pathways for eleven diarrheal diseases, seven other infectious diseases and one chemical (lead). Experts were identified through international networks followed by social network sampling. Final selection of experts was based on their experience including international working experience. Enrolled experts were scored on their ability to judge uncertainty accurately and informatively using a series of subject-matter specific 'seed' questions whose answers are unknown to the experts at the time they are interviewed. Trained facilitators elicited the 5th, and 50th and 95th percentile responses to seed questions through telephone interviews. Cooke's Classical Model uses responses to the seed questions to weigh and aggregate expert responses. After this interview, the experts were asked to provide 5th, 50th, and 95th percentile estimates for the 'target' questions regarding disease transmission routes. A total of 72 experts were enrolled in the study. Ten panels were global, meaning that the experts should provide estimates for all 14 subregions, whereas the nine panels were subregional, with experts providing estimates for one or more subregions, depending on their experience in the region. The size of the 19 hazard-specific panels ranged from 6 to 15 persons with several experts serving on more than one panel. Pathogens with animal reservoirs (e.g. non-typhoidal Salmonella spp. and Toxoplasma gondii) were in general assessed by the experts to have a higher proportion of illnesses attributable to food than pathogens with mainly a human reservoir, where human-to-human transmission (e.g. Shigella spp. and Norovirus) or waterborne transmission (e.g. Salmonella Typhi and Vibrio cholerae) were judged to dominate. For many pathogens, the foodborne route was assessed relatively more important in developed subregions than in developing subregions. The main exposure routes for lead varied across subregions, with the foodborne route being assessed most important only in two subregions of the European region. For the first time, we present worldwide estimates of the proportion of specific diseases attributable to food and other major transmission routes. These findings are essential for global burden of FBD estimates. While gaps exist, we believe the estimates presented here are the best current source of guidance to support decision makers when allocating resources for control and intervention, and for future research initiatives.

[Recommendations for terminating child custody--reasons and grounds in 30 expert decisions].

PubMed

Klosinski, G; Karle, M

1996-11-01

In a retrospective analysis 30 expert opinions on the right of visitation, which recommend the exclusion of this right for the non-custodial parent, are evaluated. These cases represent 23% of the expert opinions concerning the right of visitation that have been given by the department of Child and Adolescent Psychiatry of the University of Tübingen between 1991 and 1994. Focusing on the decisive argument for the expert to exclude the right of visitation, it became apparent that in 40% of the cases the will of the child was the determining factor, followed by sustained tension between the parents in 33% of the cases. Emotional neglect, (continuous) abuse and maltreatment (12%) as well as offences against the clause of good behaviour (Wohlverhaltensklausel) were of significant smaller influence on the decision. And although 61% of the children have been classified as psychological disturbed, only in 5% of the cases this diagnosis was of importance.

Embedded CLIPS for SDI BM/C3 simulation and analysis

NASA Technical Reports Server (NTRS)

Gossage, Brett; Nanney, Van

1990-01-01

Nichols Research Corporation is developing the BM/C3 Requirements Analysis Tool (BRAT) for the U.S. Army Strategic Defense Command. BRAT uses embedded CLIPS/Ada to model the decision making processes used by the human commander of a defense system. Embedding CLlPS/Ada in BRAT allows the user to explore the role of the human in Command and Control (C2) and the use of expert systems for automated C2. BRAT models assert facts about the current state of the system, the simulated scenario, and threat information into CLIPS/Ada. A user-defined rule set describes the decision criteria for the commander. We have extended CLIPS/Ada with user-defined functions that allow the firing of a rule to invoke a system action such as weapons release or a change in strategy. The use of embedded CLIPS/Ada will provide a powerful modeling tool for our customer at minimal cost.

Instructional Design for Advanced Learners: Training Recognition Skills to Hasten Expertise

ERIC Educational Resources Information Center

Fadde, Peter Jae

2009-01-01

Expertise in domains ranging from sports to surgery involves a process of recognition-primed decision-making (RPD) in which experts make rapid, intuitive decisions based on recognizing critical features of dynamic performance situations. While the development of expert RPD is assumed to require years of domain experience, the transition from…

Decision support system for nursing management control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ernst, C.J.

A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

Information/Knowledge Acquisition Methods for Decision Support Systems and Expert Systems.

ERIC Educational Resources Information Center

Yang, Heng-Li

1995-01-01

Compares information requirement-elicitation (IRE) methods for decision support systems (DSS) with knowledge acquisition (KA) methods for expert systems (ES) development. The definition and architectures of ES and DSS are compared and the systems' development cycles and IRE/KA methods are discussed. Differences are noted between ES and DSS…

Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task.

PubMed

Moënne-Loccoz, Cristóbal; Vergara, Rodrigo C; López, Vladimir; Mery, Domingo; Cosmelli, Diego

2017-01-01

Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve. Here we tackle the question of modeling sequential decision-making behavior in a simple human-computer interface that instantiates a 4-level binary decision tree (BDT) task. We record behavioral data from voluntary participants while they attempt to solve the task. Using a Hidden Markov Model-based approach that capitalizes on the hierarchical structure of behavior, we then model their performance during the interaction. Our results show that partitioning the problem space into a small set of hierarchically related stereotyped strategies can potentially capture a host of individual decision making policies. This allows us to follow how participants learn and develop expertise in the use of the interface. Moreover, using a Mixture of Experts based on these stereotyped strategies, the model is able to predict the behavior of participants that master the task.

[Relevance of a driving simulator in the assessment of handicapped individuals].

PubMed

Carroz, A; Comte, P-A; Nicolo, D; Dériaz, O; Vuadens, P

2008-06-01

To evaluate the value of our driving simulator in deciding whether or not to allow patients with physical and/or cognitive deficits to resuming driving and to analyze whether or not the medical expert's final decision is based more on the results of the driving simulator than those of the neuropsychological examination. One hundred and twenty-three patients were evaluated with the driving simulator. Thirty-five of those with cognitive deficits also underwent a neuropsychological examination prior to the medical expert's decision on driving aptitude. In cases of uncertainty or disagreement, a driving assessment in real conditions was performed by a driving instructor. In cases of physical handicap, the medical expert's decision concurred with that of the occupational therapist. For brain-injured patients, there was a significant correlation between the neuropsychologist's opinion and that of the occupational therapist (kappa=0.33; P=0.01). However, the sensibility and specificity were only 55 and 80%, respectively. The correlation between an occupational therapy decision based on the driving simulator and that of the medical expert was very significant (kappa=0.81; P<0.0001) and the sensibility and specificity were 84 and 100%, respectively. In contrast, these values were lower (63 and 71%, respectively) for the correlation between the neuropsychologist's opinion and that of the medical expert. Our driving simulator enables the danger-free evaluation of driving aptitude. The results mirror an in situ assessment and are more sensitive than neuropsychological examination. In fact, the neuropsychologist's opinion often is more negative or uncertain with respect to the patient's real driving aptitude. When taking a decision on a patient's driving aptitude, the medical expert is more inclined to trust the results of the driving simulator.

Modeling and Simulation of Shuttle Launch and Range Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Thirumalainambi, Rajkumar

2004-01-01

The simulation and modeling test bed is based on a mockup of a space flight operations control suitable to experiment physical, procedural, software, hardware and psychological aspects of space flight operations. The test bed consists of a weather expert system to advise on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, impact of human health risk, debris dispersion model in 3D visualization. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.

[Artificial intelligence in sleep analysis (ARTISANA)--modelling visual processes in sleep classification].

PubMed

Schwaibold, M; Schöller, B; Penzel, T; Bolz, A

2001-05-01

We describe a novel approach to the problem of automated sleep stage recognition. The ARTISANA algorithm mimics the behaviour of a human expert visually scoring sleep stages (Rechtschaffen and Kales classification). It comprises a number of interacting components that imitate the stepwise approach of the human expert, and artificial intelligence components. On the basis of parameters extracted at 1-s intervals from the signal curves, artificial neural networks recognize the incidence of typical patterns, e.g. delta activity or K complexes. This is followed by a rule interpretation stage that identifies the sleep stage with the aid of a neuro-fuzzy system while taking account of the context. Validation studies based on the records of 8 patients with obstructive sleep apnoea have confirmed the potential of this approach. Further features of the system include the transparency of the decision-taking process, and the flexibility of the option for expanding the system to cover new patterns and criteria.

Clinical decision making: how surgeons do it.

PubMed

Crebbin, Wendy; Beasley, Spencer W; Watters, David A K

2013-06-01

Clinical decision making is a core competency of surgical practice. It involves two distinct types of mental process best considered as the ends of a continuum, ranging from intuitive and subconscious to analytical and conscious. In practice, individual decisions are usually reached by a combination of each, according to the complexity of the situation and the experience/expertise of the surgeon. An expert moves effortlessly along this continuum, according to need, able to apply learned rules or algorithms to specific presentations, choosing these as a result of either pattern recognition or analytical thinking. The expert recognizes and responds quickly to any mismatch between what is observed and what was expected, coping with gaps in information and making decisions even where critical data may be uncertain or unknown. Even for experts, the cognitive processes involved are difficult to articulate as they tend to be very complex. However, if surgeons are to assist trainees in developing their decision-making skills, the processes need to be identified and defined, and the competency needs to be measurable. This paper examines the processes of clinical decision making in three contexts: making a decision about how to manage a patient; preparing for an operative procedure; and reviewing progress during an operative procedure. The models represented here are an exploration of the complexity of the processes, designed to assist surgeons understand how expert clinical decision making occurs and to highlight the challenge of teaching these skills to surgical trainees. © 2013 The Authors. ANZ Journal of Surgery © 2013 Royal Australasian College of Surgeons.

Integrating expert judgment in veterinary epidemiology: example guidance for disease freedom surveillance.

PubMed

Gustafson, L L; Gustafson, D H; Antognoli, M C; Remmenga, M D

2013-04-01

Expert opinions supplement empirical data in many epidemiologic assessments. For veterinary disease freedom surveillance, where the geographic scope of concern is often broad, populations subject to change, decisions eminent and empirical data, expert opinion can be a critical component of the decision making process. However, opinion is by definition subjective and the manner in which opinion is sought can impact the quality and reliability of estimates. Group interaction can hinder or improve the estimation process, depending on its facilitation. Further, whether and how validation is conducted can limit or increase acceptance of the resulting model. While the utility of expert opinion is widely recognized in many fields, and the impact of its use or misuse implicit, standards for application to veterinary assessments are not readily available. This paper aims to foster discussion on this influential component of epidemiology, with disease freedom application as a focus. Benefits and concerns attributed to expert judgment and guidelines for its structured elicitation are described, borrowing insights from its long history of use in decision science fields and examples from recent veterinary assessments. Published by Elsevier B.V.

Threat expert system technology advisor

NASA Technical Reports Server (NTRS)

Kurrasch, E. R.; Tripp, L. R.

1987-01-01

A prototype expert system was developed to determine the feasibility of using expert system technology to enhance the performance and survivability of helicopter pilots in a combat threat environment while flying NOE (Nap of the Earth) missions. The basis for the concept is the potential of using an Expert System Advisor to reduce the extreme overloading of the pilot who flies NOE mission below treetop level at approximately 40 knots while performing several other functions. The ultimate goal is to develop a Threat Expert System Advisor which provides threat information and advice that are better than even a highly experienced copilot. The results clearly show that the NOE pilot needs all the help in decision aiding and threat situation awareness that he can get. It clearly shows that heuristics are important and that an expert system for combat NOE helicopter missions can be of great help to the pilot in complex threat situations and in making decisions.

Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi

In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

Human Decision Processes: Implications for SSA Support Tools

NASA Astrophysics Data System (ADS)

Picciano, P.

2013-09-01

Despite significant advances in computing power and artificial intelligence (AI), few critical decisions are made without a human decision maker in the loop. Space Situational Awareness (SSA) missions are both critical and complex, typically adhering to the human-in-the-loop (HITL) model. The collection of human operators injects a needed diversity of expert knowledge, experience, and authority required to successfully fulfill SSA tasking. A wealth of literature on human decision making exists citing myriad empirical studies and offering a varied set of prescriptive and descriptive models of judgment and decision making (Hastie & Dawes, 2001; Baron, 2000). Many findings have been proven sufficiently robust to allow information architects or system/interface designers to take action to improve decision processes. For the purpose of discussion, these concepts are bifurcated in two groups: 1) vulnerabilities to mitigate, and 2) capabilities to augment. These vulnerabilities and capabilities refer specifically to the decision process and should not be confused with a shortcoming or skill of a specific human operator. Thus the framing of questions and orders, the automated tools with which to collaborate, priming and contextual data, and the delivery of information all play a critical role in human judgment and choice. Evaluating the merits of any decision can be elusive; in order to constrain this discussion, ‘rational choice' will tend toward the economic model characteristics such as maximizing utility and selection consistency (e.g., if A preferred to B, and B preferred to C, than A should be preferred to C). Simple decision models often encourage one to list the pros and cons of a decision, perhaps use a weighting schema, but one way or another weigh the future benefit (or harm) of making a selection. The result (sought by the rationalist models) should drive toward higher utility. Despite notable differences in researchers' theses (to be discussed in the full paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.

ICADS: A cooperative decision making model with CLIPS experts

NASA Technical Reports Server (NTRS)

Pohl, Jens; Myers, Leonard

1991-01-01

A cooperative decision making model is described which is comprised of six concurrently executing domain experts coordinated by a blackboard control expert. The focus application field is architectural design, and the domain experts represent consultants in the area of daylighting, noise control, structural support, cost estimating, space planning, and climate responsiveness. Both the domain experts and the blackboard were implemented as production systems, using an enhanced version of the basic CLIPS package. Acting in unison as an Expert Design Advisor, the domain and control experts react to the evolving design solution progressively developed by the user in a 2-D CAD drawing environment. A Geometry Interpreter maps each drawing action taken by the user to real world objects, such as spaces, walls, windows, and doors. These objects, endowed with geometric and nongeometric attributes, are stored as frames in a semantic network. Object descriptions are derived partly from the geometry of the drawing environment and partly from knowledge bases containing prototypical, generalized information about the building type and site conditions under consideration.

Is There a Conjunction Fallacy in Legal Probabilistic Decision Making?

PubMed

Wojciechowski, Bartosz W; Pothos, Emmanuel M

2018-01-01

Classical probability theory (CPT) has represented the rational standard for decision making in human cognition. Even though CPT has provided many descriptively excellent decision models, there have also been some empirical results persistently problematic for CPT accounts. The tension between the normative prescription of CPT and human behavior is particularly acute in cases where we have higher expectations for rational decisions. One such case concerns legal decision making from legal experts, such as attorneys and prosecutors and, more so, judges. In the present research we explore one of the most influential CPT decision fallacies, the conjunction fallacy (CF), in a legal decision making task, involving assessing evidence that the same suspect had committed two separate crimes. The information for the two crimes was presented consecutively. Each participant was asked to provide individual ratings for the two crimes in some cases and conjunctive probability rating for both crimes in other cases, after all information had been presented. Overall, 360 probability ratings for guilt were collected from 120 participants, comprised of 40 judges, 40 attorneys and prosecutors, and 40 individuals without legal education. Our results provide evidence for a double conjunction fallacy (in this case, a higher probability of committing both crimes than the probability of committing either crime individually), in the group of individuals without legal education. These results are discussed in terms of their applied implications and in relation to a recent framework for understanding such results, quantum probability theory (QPT).

Is There a Conjunction Fallacy in Legal Probabilistic Decision Making?

PubMed Central

Wojciechowski, Bartosz W.; Pothos, Emmanuel M.

2018-01-01

Classical probability theory (CPT) has represented the rational standard for decision making in human cognition. Even though CPT has provided many descriptively excellent decision models, there have also been some empirical results persistently problematic for CPT accounts. The tension between the normative prescription of CPT and human behavior is particularly acute in cases where we have higher expectations for rational decisions. One such case concerns legal decision making from legal experts, such as attorneys and prosecutors and, more so, judges. In the present research we explore one of the most influential CPT decision fallacies, the conjunction fallacy (CF), in a legal decision making task, involving assessing evidence that the same suspect had committed two separate crimes. The information for the two crimes was presented consecutively. Each participant was asked to provide individual ratings for the two crimes in some cases and conjunctive probability rating for both crimes in other cases, after all information had been presented. Overall, 360 probability ratings for guilt were collected from 120 participants, comprised of 40 judges, 40 attorneys and prosecutors, and 40 individuals without legal education. Our results provide evidence for a double conjunction fallacy (in this case, a higher probability of committing both crimes than the probability of committing either crime individually), in the group of individuals without legal education. These results are discussed in terms of their applied implications and in relation to a recent framework for understanding such results, quantum probability theory (QPT). PMID:29674983

The Use of Expert Opinion to Assess the Risk of Emergence or Re-Emergence of Infectious Diseases in Canada Associated with Climate Change

PubMed Central

Cox, Ruth; Revie, Crawford W.; Sanchez, Javier

2012-01-01

Global climate change is predicted to lead to an increase in infectious disease outbreaks. Reliable surveillance for diseases that are most likely to emerge is required, and given limited resources, policy decision makers need rational methods with which to prioritise pathogen threats. Here expert opinion was collected to determine what criteria could be used to prioritise diseases according to the likelihood of emergence in response to climate change and according to their impact. We identified a total of 40 criteria that might be used for this purpose in the Canadian context. The opinion of 64 experts from academic, government and independent backgrounds was collected to determine the importance of the criteria. A weight was calculated for each criterion based on the expert opinion. The five that were considered most influential on disease emergence or impact were: potential economic impact, severity of disease in the general human population, human case fatality rate, the type of climate that the pathogen can tolerate and the current climatic conditions in Canada. There was effective consensus about the influence of some criteria among participants, while for others there was considerable variation. The specific climate criteria that were most likely to influence disease emergence were: an annual increase in temperature, an increase in summer temperature, an increase in summer precipitation and to a lesser extent an increase in winter temperature. These climate variables were considered to be most influential on vector-borne diseases and on food and water-borne diseases. Opinion about the influence of climate on air-borne diseases and diseases spread by direct/indirect contact were more variable. The impact of emerging diseases on the human population was deemed more important than the impact on animal populations. PMID:22848536

DOE/EERE conflict-of-interest policy and form

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

2009-01-18

Conflict of interest policy and agreement recognize that 1) expert reviewers of in-progress programs do not make funding decisions, and 2) programs must often balanced perceived conflict of interest & need expert advice from small community of experts.

Heterodoxy, iconoclasm and spuriousness: the limits of novel expert evidence.

PubMed

Freckelton, Ian

2007-12-01

A difficult issue arises for courts' decision-making at common law and under statutory evidentiary regimes when expert opinions are significantly unorthodox, iconoclastic or methodologically flawed. This editorial analyses the relevant evidentiary principles and the Australian jurisprudence on the subject, giving particular attention to the decisions of the South Australian Supreme Court in R v Parenzee [2007] SASC 143 and R v Parenzee [2007] SASC 316 in which expert opinions about the existence, identifiability and transmissibility of HIV and its relationship to AIDS adduced on behalf of the defence in a criminal trial were found to be seriously wanting. A variety of factors indicative of low probative value in expert opinions are distilled.

What Is An Expert System? ERIC Digest.

ERIC Educational Resources Information Center

Boss, Richard W.

This digest describes and defines the various components of an expert system, e.g., a computerized tool designed to enhance the quality and availability of knowledge required by decision makers. It is noted that expert systems differ from conventional applications software in the following areas: (1) the existence of the expert systems shell, or…

Expert AIV: Study and Prototyping of an Expert System, To Support the Conceptual AIV Phases Of Space Programs

NASA Astrophysics Data System (ADS)

Andrina, G.; Basso, V.; Saitta, L.

2004-08-01

The effort in optimising the AIV process has been mainly focused in the recent years on the standardisation of approaches and on the application of new methodologies. But the earlier the intervention, the greater the benefits in terms of cost and schedule. Early phases of AIV process relied up to now on standards that need to be tailored through company and personal expertise. A study has then been conducted in order to exploit the possibility to develop an expert system helping in making choices in the early, conceptual phase of Assembly, Integration and Verification, namely the Model Philosophy and the test definition. The work focused on a hybrid approach, allowing interaction between historical data and human expertise. The expert system that has been prototyped exploits both information elicited from domain experts and results of a Data Mining activity on the existent data bases of completed projects verification data. The Data Mining algorithms allow the extraction of past experience resident on ESA/ MATD data base, which contains information in the form of statistical summaries, costs, frequencies of on-ground and in flight failures. Finding non-trivial associations could then be utilised by the experts to manage new decisions in a controlled way (Standards driven) at the beginning or during the AIV Process Moreover, the Expert AIV could allow compilation of a set of feasible AIV schedules to support further programmatic-driven choices.

Explanation production by expert planners

NASA Technical Reports Server (NTRS)

Bridges, Susan; Jhannes, James D.

1988-01-01

Although the explanation capability of expert systems is usually listed as one of the distinguishing characteristics of these systems, the explanation facilities of most existing systems are quite primitive. Computer generated explanations are typically produced from canned text or by direct translation of the knowledge structures. Explanations produced in this manner bear little resemblance to those produced by humans for similar tasks. The focus of our research in explanation is the production of justifications for decisions by expert planning systems. An analysis of justifications written by people for planning tasks has been taken as the starting point. The purpose of this analysis is two-fold. First, analysis of the information content of the justifications will provide a basis for deciding what knowledge must be represented if human-like justifications are to be produced. Second, an analysis of the textual organization of the justifications will be used in the development of a mechanism for selecting and organizing the knowledge to be included in a computer-produced explanation. This paper describes a preliminary analysis done of justifications written by people for a planning task. It is clear that these justifications differ significantly from those that would be produced by an expert system by tracing the firing of production rules. The results from the text analysis have been used to develop an augmented phrase structured grammar (APSG) describing the organization of the justifications. The grammar was designed to provide a computationally feasible method for determining textual organization that will allow the necessary information to be communicated in a cohesive manner.

Six Suggestions for Research on Games in Cognitive Science.

PubMed

Chabris, Christopher F

2017-04-01

Games are more varied and occupy more of daily life than ever before. At the same time, the tools available to study game play and players are more powerful than ever, especially massive data sets from online platforms and computational engines that can accurately evaluate human decisions. This essay offers six suggestions for future cognitive science research on games: (1) Don't forget about chess, (2) Look beyond action games and chess, (3) Use (near)-optimal play to understand human play and players, (4) Investigate social phenomena, (5) Raise the standards for studies of games as treatments, (6) Talk to real experts. Copyright © 2017 Cognitive Science Society, Inc.

Second CLIPS Conference Proceedings, volume 1

NASA Technical Reports Server (NTRS)

Giarratano, Joseph (Editor); Culbert, Christopher J. (Editor)

1991-01-01

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems.

How can clinical practice guidelines be adapted to facilitate shared decision making? A qualitative key-informant study.

PubMed

van der Weijden, Trudy; Pieterse, Arwen H; Koelewijn-van Loon, Marije S; Knaapen, Loes; Légaré, France; Boivin, Antoine; Burgers, Jako S; Stiggelbout, Anne M; Faber, Marjan; Elwyn, Glyn

2013-10-01

To explore how clinical practice guidelines can be adapted to facilitate shared decision making. This was a qualitative key-informant study with group discussions and semi-structured interviews. First, 75 experts in guideline development or shared decision making participated in group discussions at two international conferences. Next, health professionals known as experts in depression or breast cancer, experts on clinical practice guidelines and/or shared decision making, and patient representatives were interviewed (N=20). Using illustrative treatment decisions on depression or breast cancer, we asked the interviewees to indicate as specifically as they could how guidelines could be used to facilitate shared decision making. Interviewees suggested some generic strategies, namely to include a separate chapter on the importance of shared decision making, to use language that encourages patient involvement, and to develop patient versions of guidelines. Recommendation-specific strategies, related to specific decision points in the guideline, were also suggested: These include structuring the presentation of healthcare options to increase professionals' option awareness; structuring the deliberation process between professionals and patients; and providing relevant patient support tools embedded at important decision points in the guideline. This study resulted in an overview of strategies to adapt clinical practice guidelines to facilitate shared decision making. Some strategies seemed more contentious than others. Future research should assess the feasibility and impact of these strategies to make clinical practice guidelines more conducive to facilitate shared decision making.

An Internationally Consented Standard for Nursing Process-Clinical Decision Support Systems in Electronic Health Records.

PubMed

Müller-Staub, Maria; de Graaf-Waar, Helen; Paans, Wolter

2016-11-01

Nurses are accountable to apply the nursing process, which is key for patient care: It is a problem-solving process providing the structure for care plans and documentation. The state-of-the art nursing process is based on classifications that contain standardized concepts, and therefore, it is named Advanced Nursing Process. It contains valid assessments, nursing diagnoses, interventions, and nursing-sensitive patient outcomes. Electronic decision support systems can assist nurses to apply the Advanced Nursing Process. However, nursing decision support systems are missing, and no "gold standard" is available. The study aim is to develop a valid Nursing Process-Clinical Decision Support System Standard to guide future developments of clinical decision support systems. In a multistep approach, a Nursing Process-Clinical Decision Support System Standard with 28 criteria was developed. After pilot testing (N = 29 nurses), the criteria were reduced to 25. The Nursing Process-Clinical Decision Support System Standard was then presented to eight internationally known experts, who performed qualitative interviews according to Mayring. Fourteen categories demonstrate expert consensus on the Nursing Process-Clinical Decision Support System Standard and its content validity. All experts agreed the Advanced Nursing Process should be the centerpiece for the Nursing Process-Clinical Decision Support System and should suggest research-based, predefined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions, and patient outcomes.

Heuristic Model Of The Composite Quality Index Of Environmental Assessment

NASA Astrophysics Data System (ADS)

Khabarov, A. N.; Knyaginin, A. A.; Bondarenko, D. V.; Shepet, I. P.; Korolkova, L. N.

2017-01-01

The goal of the paper is to present the heuristic model of the composite environmental quality index based on the integrated application of the elements of utility theory, multidimensional scaling, expert evaluation and decision-making. The composite index is synthesized in linear-quadratic form, it provides higher adequacy of the results of the assessment preferences of experts and decision-makers.

Perspectives of policy and political decision makers on access to formal dementia care: expert interviews in eight European countries.

PubMed

Broda, Anja; Bieber, Anja; Meyer, Gabriele; Hopper, Louise; Joyce, Rachael; Irving, Kate; Zanetti, Orazio; Portolani, Elisa; Kerpershoek, Liselot; Verhey, Frans; Vugt, Marjolein de; Wolfs, Claire; Eriksen, Siren; Røsvik, Janne; Marques, Maria J; Gonçalves-Pereira, Manuel; Sjölund, Britt-Marie; Woods, Bob; Jelley, Hannah; Orrell, Martin; Stephan, Astrid

2017-08-03

As part of the ActifCare (ACcess to Timely Formal Care) project, we conducted expert interviews in eight European countries with policy and political decision makers, or representatives of relevant institutions, to determine their perspectives on access to formal care for people with dementia and their carers. Each ActifCare country (Germany, Ireland, Italy, The Netherlands, Norway, Portugal, Sweden, United Kingdom) conducted semi-structured interviews with 4-7 experts (total N = 38). The interview guide addressed the topics "Complexity and Continuity of Care", "Formal Services", and "Public Awareness". Country-specific analysis of interview transcripts used an inductive qualitative content analysis. Cross-national synthesis focused on similarities in themes across the ActifCare countries. The analysis revealed ten common themes and two additional sub-themes across countries. Among others, the experts highlighted the need for a coordinating role and the necessity of information to address issues of complexity and continuity of care, demanded person-centred, tailored, and multidisciplinary formal services, and referred to education, mass media and campaigns as means to raise public awareness. Policy and political decision makers appear well acquainted with current discussions among both researchers and practitioners of possible approaches to improve access to dementia care. Experts described pragmatic, realistic strategies to influence dementia care. Suggested innovations concerned how to achieve improved dementia care, rather than transforming the nature of the services provided. Knowledge gained in these expert interviews may be useful to national decision makers when they consider reshaping the organisation of dementia care, and may thus help to develop best-practice strategies and recommendations.

Microcomputer-based classification of environmental data in municipal areas

NASA Astrophysics Data System (ADS)

Thiergärtner, H.

1995-10-01

Multivariate data-processing methods used in mineral resource identification can be used to classify urban regions. Using elements of expert systems, geographical information systems, as well as known classification and prognosis systems, it is possible to outline a single model that consists of resistant and of temporary parts of a knowledge base including graphical input and output treatment and of resistant and temporary elements of a bank of methods and algorithms. Whereas decision rules created by experts will be stored in expert systems directly, powerful classification rules in form of resistant but latent (implicit) decision algorithms may be implemented in the suggested model. The latent functions will be transformed into temporary explicit decision rules by learning processes depending on the actual task(s), parameter set(s), pixels selection(s), and expert control(s). This takes place both at supervised and nonsupervised classification of multivariately described pixel sets representing municipal subareas. The model is outlined briefly and illustrated by results obtained in a target area covering a part of the city of Berlin (Germany).

Natural and Artificial Intelligence in Neurosurgery: A Systematic Review.

PubMed

Senders, Joeky T; Arnaout, Omar; Karhade, Aditya V; Dasenbrock, Hormuzdiyar H; Gormley, William B; Broekman, Marike L; Smith, Timothy R

2017-09-07

Machine learning (ML) is a domain of artificial intelligence that allows computer algorithms to learn from experience without being explicitly programmed. To summarize neurosurgical applications of ML where it has been compared to clinical expertise, here referred to as "natural intelligence." A systematic search was performed in the PubMed and Embase databases as of August 2016 to review all studies comparing the performance of various ML approaches with that of clinical experts in neurosurgical literature. Twenty-three studies were identified that used ML algorithms for diagnosis, presurgical planning, or outcome prediction in neurosurgical patients. Compared to clinical experts, ML models demonstrated a median absolute improvement in accuracy and area under the receiver operating curve of 13% (interquartile range 4-21%) and 0.14 (interquartile range 0.07-0.21), respectively. In 29 (58%) of the 50 outcome measures for which a P -value was provided or calculated, ML models outperformed clinical experts ( P < .05). In 18 of 50 (36%), no difference was seen between ML and expert performance ( P > .05), while in 3 of 50 (6%) clinical experts outperformed ML models ( P < .05). All 4 studies that compared clinicians assisted by ML models vs clinicians alone demonstrated a better performance in the first group. We conclude that ML models have the potential to augment the decision-making capacity of clinicians in neurosurgical applications; however, significant hurdles remain associated with creating, validating, and deploying ML models in the clinical setting. Shifting from the preconceptions of a human-vs-machine to a human-and-machine paradigm could be essential to overcome these hurdles. Published by Oxford University Press on behalf of Congress of Neurological Surgeons 2017.

Knowledge of Fecal Calprotectin and Infliximab Trough Levels Alters Clinical Decision-making for IBD Outpatients on Maintenance Infliximab Therapy.

PubMed

Huang, Vivian W; Prosser, Connie; Kroeker, Karen I; Wang, Haili; Shalapay, Carol; Dhami, Neil; Fedorak, Darryl K; Halloran, Brendan; Dieleman, Levinus A; Goodman, Karen J; Fedorak, Richard N

2015-06-01

Infliximab is an effective therapy for inflammatory bowel disease (IBD). However, more than 50% of patients lose response. Empiric dose intensification is not effective for all patients because not all patients have objective disease activity or subtherapeutic drug level. The aim was to determine how an objective marker of disease activity or therapeutic drug monitoring affects clinical decisions regarding maintenance infliximab therapy in outpatients with IBD. Consecutive patients with IBD on maintenance infliximab therapy were invited to participate by providing preinfusion stool and blood samples. Fecal calprotectin (FCP) and infliximab trough levels (ITLs) were measured by enzyme linked immunosorbent assay. Three decisions were compared: (1) actual clinical decision, (2) algorithmic FCP or ITL decisions, and (3) expert panel decision based on (a) clinical data, (b) clinical data plus FCP, and (c) clinical data plus FCP plus ITL. In secondary analysis, Receiver-operating curves were used to assess the ability of FCP and ITL in predicting clinical disease activity or remission. A total of 36 sets of blood and stool were available for analysis; median FCP 191.5 μg/g, median ITLs 7.3 μg/mL. The actual clinical decision differed from the hypothetical decision in 47.2% (FCP algorithm); 69.4% (ITL algorithm); 25.0% (expert panel clinical decision); 44.4% (expert panel clinical plus FCP); 58.3% (expert panel clinical plus FCP plus ITL) cases. FCP predicted clinical relapse (area under the curve [AUC] = 0.417; 95% confidence interval [CI], 0.197-0.641) and subtherapeutic ITL (AUC = 0.774; 95% CI, 0.536-1.000). ITL predicted clinical remission (AUC = 0.498; 95% CI, 0.254-0.742) and objective remission (AUC = 0.773; 95% CI, 0.622-0.924). Using FCP and ITLs in addition to clinical data results in an increased number of decisions to optimize management in outpatients with IBD on stable maintenance infliximab therapy.

A new intelligent electronic nose system for measuring and analysing livestock and poultry farm odours.

PubMed

Pan, Leilei; Yang, Simon X

2007-12-01

This paper introduces a new portable intelligent electronic nose system developed especially for measuring and analysing livestock and poultry farm odours. It can be used in both laboratory and field. The sensor array of the proposed electronic nose consists of 14 gas sensors, a humidity sensor, and a temperature sensor. The gas sensors were especially selected for the main compounds from the livestock farm odours. An expert system called "Odour Expert" was developed to support researchers' and farmers' decision making on odour control strategies for livestock and poultry operations. "Odour Expert" utilises several advanced artificial intelligence technologies tailored to livestock and poultry farm odours. It can provide more advanced odour analysis than existing commercially available products. In addition, a rank of odour generation factors is provided, which refines the focus of odour control research. Field experiments were conducted downwind from the barns on 14 livestock and poultry farms. Experimental results show that the predicted odour strengths by the electronic nose yield higher consistency in comparison to the perceived odour intensity by human panel. The "Odour Expert" is a useful tool for assisting farmers' odour management practises.

Naturalistic decision-making in expert badminton players.

PubMed

Macquet, A C; Fleurance, P

2007-09-01

This paper reports on a study of naturalistic decision-making in expert badminton players. These decisions are frequently taken under time-pressured conditions, yet normally lead to successful performance. Two male badminton teams participated in this study. Self-confrontation interviews were used to collect data. Inductive data analysis revealed three types of intentions during a rally: to maintain the rally; to take the advantage; and to finish the point. It also revealed eight types of decision taken in this situation: to ensure an action; to observe the opponent's response to an action; to realize a limited choice; to influence the opponent's decision; to put pressure on an opponent; to surprise the opponent; to reproduce an efficient action; and to play wide. A frequent decision was to put pressure on the opponent. Different information and knowledge was linked to specific decisions. The results are discussed in relation to research that has considered naturalistic decision-making.

Operation and Structure of an Artificial Intelligence Expert Consultative System for Reading and Learning.

ERIC Educational Resources Information Center

Balajthy, Ernest

1989-01-01

The article examines decision-making expert systems and discusses their implications for diagnosis and prescription of reading difficulties. A detailed description of how a reading diagnostic expert system might operate to aid classroom teachers is followed by a discussion of advantages and limitations of expert systems for educational use.…

EXSPRT: An Expert Systems Approach to Computer-Based Adaptive Testing.

ERIC Educational Resources Information Center

Frick, Theodore W.; And Others

Expert systems can be used to aid decision making. A computerized adaptive test (CAT) is one kind of expert system, although it is not commonly recognized as such. A new approach, termed EXSPRT, was devised that combines expert systems reasoning and sequential probability ratio test stopping rules. EXSPRT-R uses random selection of test items,…

Missing focus on Human Factors – organizational and cognitive ergonomics – in the safety management for the petroleum industry

PubMed Central

Johnsen, Stig O; Kilskar, Stine Skaufel; Fossum, Knut Robert

2017-01-01

More attention has recently been given to Human Factors in petroleum accident investigations. The Human Factors areas examined in this article are organizational, cognitive and physical ergonomics. A key question to be explored is as follows: To what degree are the petroleum industry and safety authorities in Norway focusing on these Human Factors areas from the design phase? To investigate this, we conducted an innovative exploratory study of the development of four control centres in Norwegian oil and gas industry in collaboration between users, management and Human Factors experts. We also performed a literature survey and discussion with the professional Human Factors network in Norway. We investigated the Human Factors focus, reasons for not considering Human Factors and consequences of missing Human Factors in safety management. The results revealed an immature focus and organization of Human Factors. Expertise on organizational ergonomics and cognitive ergonomics are missing from companies and safety authorities and are poorly prioritized during the development. The easy observable part of Human Factors (i.e. physical ergonomics) is often in focus. Poor focus on Human Factors in the design process creates demanding conditions for human operators and impact safety and resilience. There is lack of non-technical skills such as communication and decision-making. New technical equipment such as Closed Circuit Television is implemented without appropriate use of Human Factors standards. Human Factors expertise should be involved as early as possible in the responsible organizations. Verification and validation of Human Factors should be improved and performed from the start, by certified Human Factors experts in collaboration with the workforce. The authorities should check-back that the regulatory framework of Human Factors is communicated, understood and followed. PMID:29278242

An fMRI and effective connectivity study investigating miss errors during advice utilization from human and machine agents.

PubMed

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; de Visser, Ewart; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2017-10-01

As society becomes more reliant on machines and automation, understanding how people utilize advice is a necessary endeavor. Our objective was to reveal the underlying neural associations during advice utilization from expert human and machine agents with fMRI and multivariate Granger causality analysis. During an X-ray luggage-screening task, participants accepted or rejected good or bad advice from either the human or machine agent framed as experts with manipulated reliability (high miss rate). We showed that the machine-agent group decreased their advice utilization compared to the human-agent group and these differences in behaviors during advice utilization could be accounted for by high expectations of reliable advice and changes in attention allocation due to miss errors. Brain areas involved with the salience and mentalizing networks, as well as sensory processing involved with attention, were recruited during the task and the advice utilization network consisted of attentional modulation of sensory information with the lingual gyrus as the driver during the decision phase and the fusiform gyrus as the driver during the feedback phase. Our findings expand on the existing literature by showing that misses degrade advice utilization, which is represented in a neural network involving salience detection and self-processing with perceptual integration.

Bioethical ambition, political opportunity and the European governance of patenting: the case of human embryonic stem cell science.

PubMed

Salter, Brian; Salter, Charlotte

2013-12-01

Scientific progress in the life sciences is dependent on the governance of tensions between the economic potential of the innovation and the cultural response from society. Ownership of the scientific innovation through patenting is a necessary part of the realization of its economic value yet, in the case of human embryonic stem cell (hESC) science, ownership of the human body and human life may offend fundamental cultural values. In the case of transnational patenting governance by the European Patent Office (EPO) and the European Union (EU), cross-national cultural conflict in the field of hESC science has produced a political demand for a form of governance that can incorporate ethical as well as economic judgements in its decision making. This paper explores how bioethics has responded to this opportunity to establish itself as a form of expert authority for the negotiation and resolution of the cultural conflict. In so doing, it shows how the political struggle that has accompanied this bid for new governance territory has been influenced both by the political tensions between the EPO and EU systems of patenting governance and the resistance of competing experts in law and science to a bioethical presence. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bioethics governance in Israel: an expert regime.

PubMed

Shalev, Carmel; Hashiloni-Dolev, Yael

2011-01-01

This paper provides an overview of bioethics governance in Israel through an analytical description of the legal framework for the interface between individuals and biomedical practices. There is no national agency with general oversight of bioethics policy and decision making, and the rules that apply to individual usage of biomedical technologies are laid down in a multitude of different statutes, regulations and administrative directives. Expert committees play a central role in this regulatory system in two capacities: as governmental advisory bodies that recommend policy; and as decision-making bodies that resolve conflicts around patients' rights or grant individual access to biomedical technologies. This decentralised system of governance through expert committees allows for adaptation to dynamic technological developments and flexibility in accommodating creative societal usage. At the same time the experts are the agents of the state's bio-power at the expense of personal autonomy and open public deliberation. The paper is part of a larger study investigating Israel's bioethics governance and its regime of experts, which includes an examination of the normative level of regulation, and an analysis of the composition of the expert committees. Our findings suggest that Israel has a decentralised system of governance with piecemeal regulation that has established a bioethics technocracy, governed by the ministry of health and dominated by the medical profession. The present paper is confined to a description and discussion of the legal framework of Israel's expert bioethics regime. Here, our major conclusion is that Israel has established a technocracy of official expert ethics committees, which controls life and death decisions.

Design and implementation of expert decision system in Yellow River Irrigation

NASA Astrophysics Data System (ADS)

Fuping, Wang; Bingbing, Lei; Jie, Pan

2018-03-01

How to make full use of water resources in the Yellow River irrigation is a problem needed to be solved urgently. On account of the different irrigation strategies in various growth stages of wheat, this paper proposes a novel irrigation expert decision system basing on fuzzy control technique. According to the control experience, expert knowledge and MATLAB simulation optimization, we obtain the irrigation fuzzy control table stored in the computer memory. The controlling irrigation is accomplished by reading the data from fuzzy control table. The experimental results show that the expert system can be used in the production of wheat to achieve timely and appropriate irrigation, and ensure that wheat growth cycle is always in the best growth environment.

Opening the Black Box: Cognitive Strategies in Family Practice

PubMed Central

Christensen, Robert E.; Fetters, Michael D.; Green, Lee A.

2005-01-01

PURPOSE We wanted to describe the cognitive strategies used by family physicians when structuring the decision-making tasks of an outpatient visit. METHODS This qualitative study used cognitive task analysis, a structured interview method in which a trained interviewer works individually with expert decision makers to capture their stages and elements of information processing. RESULTS Eighteen family physicians of varying levels of experience participated. Three dominant themes emerged: time pressure, a high degree of variation in task structuring, and varying degrees of task automatization. Based on these data and previous research from the cognitive sciences, we developed a model of novice and expert approaches to decision making in primary care. The model illustrates differences in responses to unexpected opportunity in practice, particularly the expert’s use of attentional surplus (reserve capacity to handle problems) vs the novice’s choice between taking more time or displacing another task. CONCLUSIONS Family physicians have specific, highly individualized cognitive task-structuring approaches and show the decision behavior features typical of expert decision makers in other fields. This finding places constraints on and suggests useful approaches for improving practice. PMID:15798041

Combining Decision Rules from Classification Tree Models and Expert Assessment to Estimate Occupational Exposure to Diesel Exhaust for a Case-Control Study

PubMed Central

Friesen, Melissa C.; Wheeler, David C.; Vermeulen, Roel; Locke, Sarah J.; Zaebst, Dennis D.; Koutros, Stella; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Malats, Nuria; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Rothman, Nathanial; Stewart, Patricia A.; Kogevinas, Manolis; Silverman, Debra T.

2016-01-01

Objectives: To efficiently and reproducibly assess occupational diesel exhaust exposure in a Spanish case-control study, we examined the utility of applying decision rules that had been extracted from expert estimates and questionnaire response patterns using classification tree (CT) models from a similar US study. Methods: First, previously extracted CT decision rules were used to obtain initial ordinal (0–3) estimates of the probability, intensity, and frequency of occupational exposure to diesel exhaust for the 10 182 jobs reported in a Spanish case-control study of bladder cancer. Second, two experts reviewed the CT estimates for 350 jobs randomly selected from strata based on each CT rule’s agreement with the expert ratings in the original study [agreement rate, from 0 (no agreement) to 1 (perfect agreement)]. Their agreement with each other and with the CT estimates was calculated using weighted kappa (κ w) and guided our choice of jobs for subsequent expert review. Third, an expert review comprised all jobs with lower confidence (low-to-moderate agreement rates or discordant assignments, n = 931) and a subset of jobs with a moderate to high CT probability rating and with moderately high agreement rates (n = 511). Logistic regression was used to examine the likelihood that an expert provided a different estimate than the CT estimate based on the CT rule agreement rates, the CT ordinal rating, and the availability of a module with diesel-related questions. Results: Agreement between estimates made by two experts and between estimates made by each of the experts and the CT estimates was very high for jobs with estimates that were determined by rules with high CT agreement rates (κ w: 0.81–0.90). For jobs with estimates based on rules with lower agreement rates, moderate agreement was observed between the two experts (κ w: 0.42–0.67) and poor-to-moderate agreement was observed between the experts and the CT estimates (κ w: 0.09–0.57). In total, the expert review of 1442 jobs changed 156 probability estimates, 128 intensity estimates, and 614 frequency estimates. The expert was more likely to provide a different estimate when the CT rule agreement rate was <0.8, when the CT ordinal ratings were low to moderate, or when a module with diesel questions was available. Conclusions: Our reliability assessment provided important insight into where to prioritize additional expert review; as a result, only 14% of the jobs underwent expert review, substantially reducing the exposure assessment burden. Overall, we found that we could efficiently, reproducibly, and reliably apply CT decision rules from one study to assess exposure in another study. PMID:26732820

Web-based Weather Expert System (WES) for Space Shuttle Launch

NASA Technical Reports Server (NTRS)

Bardina, Jorge E.; Rajkumar, T.

2003-01-01

The Web-based Weather Expert System (WES) is a critical module of the Virtual Test Bed development to support 'go/no go' decisions for Space Shuttle operations in the Intelligent Launch and Range Operations program of NASA. The weather rules characterize certain aspects of the environment related to the launching or landing site, the time of the day or night, the pad or runway conditions, the mission durations, the runway equipment and landing type. Expert system rules are derived from weather contingency rules, which were developed over years by NASA. Backward chaining, a goal-directed inference method is adopted, because a particular consequence or goal clause is evaluated first, and then chained backward through the rules. Once a rule is satisfied or true, then that particular rule is fired and the decision is expressed. The expert system is continuously verifying the rules against the past one-hour weather conditions and the decisions are made. The normal procedure of operations requires a formal pre-launch weather briefing held on Launch minus 1 day, which is a specific weather briefing for all areas of Space Shuttle launch operations. In this paper, the Web-based Weather Expert System of the Intelligent Launch and range Operations program is presented.

Expertise and age differences in pilot decision making.

PubMed

Morrow, Daniel G; Miller, Lisa M Soederberg; Ridolfo, Heather E; Magnor, Clifford; Fischer, Ute M; Kokayeff, Nina K; Stine-Morrow, Elizabeth A L

2009-01-01

We examined the influence of age and expertise on pilot decision making. Older and younger expert and novice pilots read at their own pace scenarios describing simpler or more complex flight situations. Then in a standard interview they discussed the scenario problem and how they would respond. Protocols were coded for identification of problem and solutions to this problem, and frequency of elaborations on problem and solution. Scenario comprehension was measured as differential reading time allocation to problem-critical information and scenario memory by the accuracy of answering questions about the scenarios after the interview. All groups accurately identified the problems, but experts elaborated problem descriptions more than novices did. Experts also spent more time reading critical information in the complex scenarios, which may reflect time needed to develop elaborate situation models of the problems. Expertise comprehension benefits were similar for older and younger pilots. Older experts were especially likely to elaborate the problem compared to younger experts, while older novices were less likely to elaborate the problem and to identify appropriate solutions compared to their younger counterparts. The findings suggest age invariance in knowledge-based comprehension relevant to pilot decision making.

Safety Tips from the Expert Witness.

ERIC Educational Resources Information Center

Gray, Gary R.

1995-01-01

Many physical educators and coaches use the potential for liability to guide their decisions about conducting activities. By understanding expert witnesses' roles in negligence actions, surer planning, teaching, and coaching are possible. The paper describes issues that expert witnesses examine in negligence actions against physical educators,…

Expert systems as applied to bridges and pavements : an overview.

DOT National Transportation Integrated Search

1986-01-01

Expert systems is a rapidly emerging new application of computers to aid decision makers in solving problems. This report gives an overview of what expert systems are and of what use they may be to a transportation department. The focus of the applic...

Gold-standard for computer-assisted morphological sperm analysis.

PubMed

Chang, Violeta; Garcia, Alejandra; Hitschfeld, Nancy; Härtel, Steffen

2017-04-01

Published algorithms for classification of human sperm heads are based on relatively small image databases that are not open to the public, and thus no direct comparison is available for competing methods. We describe a gold-standard for morphological sperm analysis (SCIAN-MorphoSpermGS), a dataset of sperm head images with expert-classification labels in one of the following classes: normal, tapered, pyriform, small or amorphous. This gold-standard is for evaluating and comparing known techniques and future improvements to present approaches for classification of human sperm heads for semen analysis. Although this paper does not provide a computational tool for morphological sperm analysis, we present a set of experiments for comparing sperm head description and classification common techniques. This classification base-line is aimed to be used as a reference for future improvements to present approaches for human sperm head classification. The gold-standard provides a label for each sperm head, which is achieved by majority voting among experts. The classification base-line compares four supervised learning methods (1- Nearest Neighbor, naive Bayes, decision trees and Support Vector Machine (SVM)) and three shape-based descriptors (Hu moments, Zernike moments and Fourier descriptors), reporting the accuracy and the true positive rate for each experiment. We used Fleiss' Kappa Coefficient to evaluate the inter-expert agreement and Fisher's exact test for inter-expert variability and statistical significant differences between descriptors and learning techniques. Our results confirm the high degree of inter-expert variability in the morphological sperm analysis. Regarding the classification base line, we show that none of the standard descriptors or classification approaches is best suitable for tackling the problem of sperm head classification. We discovered that the correct classification rate was highly variable when trying to discriminate among non-normal sperm heads. By using the Fourier descriptor and SVM, we achieved the best mean correct classification: only 49%. We conclude that the SCIAN-MorphoSpermGS will provide a standard tool for evaluation of characterization and classification approaches for human sperm heads. Indeed, there is a clear need for a specific shape-based descriptor for human sperm heads and a specific classification approach to tackle the problem of high variability within subcategories of abnormal sperm cells. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fuzzy logic based expert system for the treatment of mobile tooth.

PubMed

Mago, Vijay Kumar; Mago, Anjali; Sharma, Poonam; Mago, Jagmohan

2011-01-01

The aim of this research work is to design an expert system to assist dentist in treating the mobile tooth. There is lack of consistency among dentists in choosing the treatment plan. Moreover, there is no expert system currently available to verify and support such decision making in dentistry. A Fuzzy Logic based expert system has been designed to accept imprecise and vague values of dental sign-symptoms related to mobile tooth and the system suggests treatment plan(s). The comparison of predictions made by the system with those of the dentist is conducted. Chi-square Test of homogeneity is conducted and it is found that the system is capable of predicting accurate results. With this system, dentist feels more confident while planning the treatment of mobile tooth as he can verify his decision with the expert system. The authors also argue that Fuzzy Logic provides an appropriate mechanism to handle imprecise values of dental domain.

Including values in evidence-based policy making for breast screening: An empirically grounded tool to assist expert decision makers.

PubMed

Parker, Lisa

2017-07-01

Values are an important part of evidence-based decision making for health policy: they guide the type of evidence that is collected, how it is interpreted, and how important the conclusions are considered to be. Experts in breast screening (including clinicians, researchers, consumer advocates and senior administrators) hold differing values in relation to what is important in breast screening policy and practice, and committees may find it difficult to incorporate the complexity and variety of values into policy decisions. The decision making tool provided here is intended to assist with this process. The tool is modified from more general frameworks that are intended to assist with ethical decision making in public health, and informed by data drawn from previous empirical studies on values amongst Australian breast screening experts. It provides a structured format for breast screening committees to consider and discuss the values of themselves and others, suggests relevant topics for further inquiry and highlights areas of need for future research into the values of the public. It enables committees to publicly explain and justify their decisions with reference to values, improving transparency and accountability. It is intended to act alongside practices that seek to accommodate the values of individual women in the informed decision making process for personal decision making about participation in breast screening. Copyright © 2017 Elsevier B.V. All rights reserved.

A Subjective Assessment of Alternative Mission Architecture Operations Concepts for the Human Exploration of Mars at NASA Using a Three-Dimensional Multi-Criteria Decision Making Model

NASA Technical Reports Server (NTRS)

Tavana, Madjid

2003-01-01

The primary driver for developing missions to send humans to other planets is to generate significant scientific return. NASA plans human planetary explorations with an acceptable level of risk consistent with other manned operations. Space exploration risks can not be completely eliminated. Therefore, an acceptable level of cost, technical, safety, schedule, and political risks and benefits must be established for exploratory missions. This study uses a three-dimensional multi-criteria decision making model to identify the risks and benefits associated with three alternative mission architecture operations concepts for the human exploration of Mars identified by the Mission Operations Directorate at Johnson Space Center. The three alternatives considered in this study include split, combo lander, and dual scenarios. The model considers the seven phases of the mission including: 1) Earth Vicinity/Departure; 2) Mars Transfer; 3) Mars Arrival; 4) Planetary Surface; 5) Mars Vicinity/Departure; 6) Earth Transfer; and 7) Earth Arrival. Analytic Hierarchy Process (AHP) and subjective probability estimation are used to captures the experts belief concerning the risks and benefits of the three alternative scenarios through a series of sequential, rational, and analytical processes.

Individual versus group decision making: Jurors' reliance on central and peripheral information to evaluate expert testimony.

PubMed

Salerno, Jessica M; Bottoms, Bette L; Peter-Hagene, Liana C

2017-01-01

To investigate dual-process persuasion theories in the context of group decision making, we studied low and high need-for-cognition (NFC) participants within a mock trial study. Participants considered plaintiff and defense expert scientific testimony that varied in argument strength. All participants heard a cross-examination of the experts focusing on peripheral information (e.g., credentials) about the expert, but half were randomly assigned to also hear central information highlighting flaws in the expert's message (e.g., quality of the research presented by the expert). Participants rendered pre- and post-group-deliberation verdicts, which were considered "scientifically accurate" if the verdicts reflected the strong (versus weak) expert message, and "scientifically inaccurate" if they reflected the weak (versus strong) expert message. For individual participants, we replicated studies testing classic persuasion theories: Factors promoting reliance on central information (i.e., central cross-examination, high NFC) improved verdict accuracy because they sensitized individual participants to the quality discrepancy between the experts' messages. Interestingly, however, at the group level, the more that scientifically accurate mock jurors discussed peripheral (versus central) information about the experts, the more likely their group was to reach the scientifically accurate verdict. When participants were arguing for the scientifically accurate verdict consistent with the strong expert message, peripheral comments increased their persuasiveness, which made the group more likely to reach the more scientifically accurate verdict.

Development of an instructional expert system for hole drilling processes

NASA Technical Reports Server (NTRS)

Al-Mutawa, Souhaila; Srinivas, Vijay; Moon, Young Bai

1990-01-01

An expert system which captures the expertise of workshop technicians in the drilling domain was developed. The expert system is aimed at novice technicians who know how to operate the machines but have not acquired the decision making skills that are gained with experience. This paper describes the domain background and the stages of development of the expert system.

Organization of Programming Knowledge of Novices and Experts.

ERIC Educational Resources Information Center

Wiedenbeck, Susan

1986-01-01

Reports on an experiment where novice and expert programmers made decisions about Fortran code segments. The results show that, although expert programmers are better able to extract and use functional information, they don't differ significantly from novices in their ability to use syntactic concepts. (Author/EM)

Clinical Decision-Making in Community Children's Mental Health: Using Innovative Methods to Compare Clinicians With and Without Training in Evidence-Based Treatment.

PubMed

Baker-Ericzén, Mary J; Jenkins, Melissa M; Park, Soojin; Garland, Ann F

2015-02-01

Mental health professionals' decision-making practice is an area of increasing interest and importance, especially in the pediatric research and clinical communities. The present study explored the role of prior training in evidence-based treatments on clinicians' assessment and treatment formulations using case vignettes. Specifically, study aims included using the Naturalistic Decision Making (NDM) cognitive theory to 1) examine potential associations between EBT training and decision-making processes (novice versus expert type), and 2) explore how client and family contextual information affects clinical decision-making. Forty-eight clinicians across two groups (EBT trained=14, Not EBT trained=34) participated. Clinicians were comparable on professional experience, demographics, and discipline. The quasi-experimental design used an analog "think aloud" method where clinicians read case vignettes about a child with disruptive behavior problems and verbalized case conceptualization and treatment planning out-loud. Responses were coded according to NDM theory. MANOVA results were significant for EBT training status such that EBT trained clinicians' displayed cognitive processes more closely aligned with "expert" decision-makers and non-EBT trained clinicians' decision processes were more similar to "novice" decision-makers, following NDM theory. Non-EBT trained clinicians assigned significantly more diagnoses, provided less detailed treatment plans and discussed fewer EBTs. Parent/family contextual information also appeared to influence decision-making. This study offers a preliminary investigation of the possible broader impacts of EBT training and potential associations with development of expert decision-making skills. Targeting clinicians' decision-making may be an important avenue to pursue within dissemination-implementation efforts in mental health practice.

Expert system for neurosurgical treatment planning

NASA Astrophysics Data System (ADS)

Cheng, Andrew Y. S.; Chung, Sally S. Y.; Kwok, John C. K.

1996-04-01

A specially designed expert system is in development for neurosurgical treatment planning. The knowledge base contains knowledge and experiences on neurosurgical treatment planning from neurosurgeon consultants, who also determine the risks of different regions in human brains. When completed, the system can simulate the decision making process of neurosurgeons to determine the safest probing path for operation. The Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scan images for each patient are grabbed as the input. The system also allows neurosurgeons to include for any particular patient the additional information, such as how the tumor affects its neighboring functional regions, which is also important for calculating the safest probing path. It can then consider all the relevant information and find the most suitable probing path on the patient's brain. A 3D brain model is constructed for each set of the CT/MRI scan images and is displayed real-time together with the possible probing paths found. The precise risk value of each path is shown as a number between 0 and 1, together with its possible damages in text. Neurosurgeons can view more than one possible path simultaneously, and make the final decision on the selected path for operation.

Computer assisted diagnosis in renal nuclear medicine: rationale, methodology and interpretative criteria for diuretic renography

PubMed Central

Taylor, Andrew T; Garcia, Ernest V

2014-01-01

The goal of artificial intelligence, expert systems, decision support systems and computer assisted diagnosis (CAD) in imaging is the development and implementation of software to assist in the detection and evaluation of abnormalities, to alert physicians to cognitive biases, to reduce intra and inter-observer variability and to facilitate the interpretation of studies at a faster rate and with a higher level of accuracy. These developments are needed to meet the challenges resulting from a rapid increase in the volume of diagnostic imaging studies coupled with a concurrent increase in the number and complexity of images in each patient data. The convergence of an expanding knowledge base and escalating time constraints increases the likelihood of physician errors. Errors are even more likely when physicians interpret low volume studies such as 99mTc-MAG3 diuretic scans where imagers may have had limited training or experience. Decision support systems include neural networks, case-based reasoning, expert systems and statistical systems. iRENEX (renal expert) is an expert system for diuretic renography that uses a set of rules obtained from human experts to analyze a knowledge base of both clinical parameters and quantitative parameters derived from the renogram. Initial studies have shown that the interpretations provided by iRENEX are comparable to the interpretations of a panel of experts. iRENEX provides immediate patient specific feedback at the time of scan interpretation, can be queried to provide the reasons for its conclusions and can be used as an educational tool to teach trainees to better interpret renal scans. iRENEX also has the capacity to populate a structured reporting module and generate a clear and concise impression based on the elements contained in the report; adherence to the procedural and data entry components of the structured reporting module assures and documents procedural competency. Finally, although the focus is CAD applied to diuretic renography, this review offers a window into the rationale, methodology and broader applications of computer assisted diagnosis in medical imaging. PMID:24484751

Artificial intelligence against breast cancer (A.N.N.E.S-B.C.-Project).

PubMed

Parmeggiani, Domenico; Avenia, Nicola; Sanguinetti, Alessandro; Ruggiero, Roberto; Docimo, Giovanni; Siciliano, Mattia; Ambrosino, Pasquale; Madonna, Imma; Peltrini, Roberto; Parmeggiani, Umberto

2012-01-01

Our preliminary study examined the development of an advanced innovative technology with the objectives of--developing methodologies and algorithms for a Artificial Neural Network (ANN) system, improving mammography and ultra-sonography images interpretation;--creating autonomous software as a diagnostic tool for the physicians, allowing the possibility for the advanced application of databases using Artificial Intelligence (Expert System). Since 2004 550 F patients over 40 yrs old were divided in two groups: 1) 310 pts underwent echo every 6 months and mammography every year by expert radiologists. 2) 240 pts had the same screening program and were also examined by our diagnosis software, developed with ANN-ES technology by the Engineering Aircraft Research Project team. The information was continually updated and returned to the Expert System, defining the principal rules of automatic diagnosis. In the second group we selected: Expert radiologist decision; ANN-ES decision; Expert radiologists with ANN-ES decision. The second group had significantly better diagnosis for cancer and better specificity for breast lesions risk as well as the highest percentage account when the radiologist's decision was helped by the ANN software. The ANN-ES group was able to select, by anamnestic, diagnostic and genetic means, 8 patients for prophylactic surgery, finding 4 cancers in a very early stage. Although it is only a preliminary study, this innovative diagnostic tool seems to provide better positive and negative predictive value in cancer diagnosis as well as in breast risk lesion identification.

Expert Elicitation of Multinomial Probabilities for Decision-Analytic Modeling: An Application to Rates of Disease Progression in Undiagnosed and Untreated Melanoma.

PubMed

Wilson, Edward C F; Usher-Smith, Juliet A; Emery, Jon; Corrie, Pippa G; Walter, Fiona M

2018-06-01

Expert elicitation is required to inform decision making when relevant "better quality" data either do not exist or cannot be collected. An example of this is to inform decisions as to whether to screen for melanoma. A key input is the counterfactual, in this case the natural history of melanoma in patients who are undiagnosed and hence untreated. To elicit expert opinion on the probability of disease progression in patients with melanoma that is undetected and hence untreated. A bespoke webinar-based expert elicitation protocol was administered to 14 participants in the United Kingdom, Australia, and New Zealand, comprising 12 multinomial questions on the probability of progression from one disease stage to another in the absence of treatment. A modified Connor-Mosimann distribution was fitted to individual responses to each question. Individual responses were pooled using a Monte-Carlo simulation approach. Participants were asked to provide feedback on the process. A pooled modified Connor-Mosimann distribution was successfully derived from participants' responses. Feedback from participants was generally positive, with 86% willing to take part in such an exercise again. Nevertheless, only 57% of participants felt that this was a valid approach to determine the risk of disease progression. Qualitative feedback reflected some understanding of the need to rely on expert elicitation in the absence of "hard" data. We successfully elicited and pooled the beliefs of experts in melanoma regarding the probability of disease progression in a format suitable for inclusion in a decision-analytic model. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Multi-criteria decision analysis for health technology assessment in Canada: insights from an expert panel discussion.

PubMed

Diaby, Vakaramoko; Goeree, Ron; Hoch, Jeffrey; Siebert, Uwe

2015-02-01

Multi-criteria decision analysis (MCDA), a decision-making tool, has received increasing attention in recent years, notably in the healthcare field. For Canada, it is unclear whether and how MCDA should be incorporated into the existing health technology assessment (HTA) decision-making process. To facilitate debate on improving HTA decision-making in Canada, a workshop was held in conjunction with the 8th World Congress on Health Economics of the International Health Economics Association in Toronto, Canada in July 2011. The objective of the workshop was to discuss the potential benefits and challenges related to the use of MCDA for HTA decision-making in Canada. This paper summarizes and discusses the recommendations of an expert panel convened at the workshop to discuss opportunities and concerns with reference to the implementation of MCDA in Canada.

Expert stakeholder attitudes and support for alternative water sources in a groundwater depleted region.

PubMed

Boyer, Treavor H; Overdevest, Christine; Christiansen, Lisa; Ishii, Stephanie K L

2012-10-15

The main objectives of this research were to quantify the risks/benefits and impacts of alternative water sources (AWSs) as perceived by expert stakeholders and to evaluate the overall support for multiple AWSs by expert stakeholders. The St. Johns River (SJR) basin, FL, USA was chosen as a case study for AWSs because it is a fresh groundwater depleted region and there are ongoing activities related to water supply planning. Expert stakeholders included federal, state, and local governments, public utilities, consulting engineering and industry, and environmental and social non-governmental organizations. AWSs under consideration in the SJR basin include surface water, desalination, water reclamation, and water conservation. A two-phase research approach was followed that focused on expert stakeholders. First, an elicitation study was used to identify salient beliefs about AWSs. Open-ended questions were asked about the risks/benefits of AWSs in terms of the three pillars of sustainability: ecological, economic, and human health impacts. Second, an online survey was constructed using beliefs identified during the elicitation study. The online survey was used to quantify attitudes toward and overall support for AWSs. The salient beliefs of expert stakeholders were dominated by the ecological pillar of sustainability. The support of expert stakeholders for AWSs, from least favorable to most favorable, was surface water withdrawals

Adjusting Beliefs via Transformed Fuzzy Priors

NASA Astrophysics Data System (ADS)

Rattanadamrongaksorn, T.; Sirikanchanarak, D.; Sirisrisakulchai, J.; Sriboonchitta, S.

2018-02-01

Instead of leaving a decision to a pure data-driven system, intervention and collaboration by human would be preferred to fill the gap that machine cannot perform well. In financial applications, for instance, the inference and prediction during structural changes by critical factors; such as market conditions, administrative styles, political policies, etc.; have significant influences to investment strategies. With the conditions differing from the past, we believe that the decision should not be made by only the historical data but also with human estimation. In this study, the updating process by data fusion between expert opinions and statistical observations is thus proposed. The expert’s linguistic terms can be translated into mathematical expressions by the predefined fuzzy numbers and utilized as the initial knowledge for Bayesian statistical framework via the possibility-to-probability transformation. The artificial samples on five scenarios were tested in the univariate problem to demonstrate the methodology. The results showed the shifts and variations appeared on the parameters of the distributions and, as a consequence, adjust the degrees of belief accordingly.

Political rape as persecution: a legal perspective.

PubMed

Kelly, N

1997-01-01

The use of rape as a tool of persecution is not new, but recognition of the political rape of women as a violation of internationally protected human rights and as a basis for political asylum is. Over the last several years, a number of advances have been made, including human rights instruments that recognize the need to protect women from rape and other sexual abuse; guidelines from the United Nations High Commission for Refugees and several countries that acknowledge the political nature of rape and the difficulties experienced by women attempting to assert claims to asylum based on rape or other sexual abuse; and a number of important decisions by individual governments to provide protection to survivors of rape. Legal advancements for women in this area have depended largely on the assistance of medical and psychological experts who have been able to educate adjudicators and advocates on the effects of sexual harm, provide expert testimony in individual asylum cases, and provide critical treatment and support to survivors as they work their way through the process of obtaining legal protection.

Automation Diagnosis of Skin Disease in Humans using Dempster-Shafer Method

NASA Astrophysics Data System (ADS)

Khairina, Dyna Marisa; Hatta, Heliza Rahmania; Rustam; Maharani, Septya

2018-02-01

Skin disease is an infectious disease that is common in people of all ages. Disorders of the skin often occur because there are factors, among others, are climate, environment, shelter, unhealthy living habits, allergies and others. Skin diseases in Indonesia are mostly caused by bacterial, fungal, parasitic, and allergies. The objective of the research is to diagnose skin diseases in humans by using the method of making decision tree then performing the search by forward chaining and calculating the probability value of Dempster-Shafer method. The results of research in the form of an automated system that can resemble an expert in diagnosing skin disease accurately and can help in overcoming the problem of skin diseases.

Robotic astrobiology - prospects for enhancing scientific productivity of mars rover missions

NASA Astrophysics Data System (ADS)

Ellery, A. A.

2018-07-01

Robotic astrobiology involves the remote projection of intelligent capabilities to planetary missions in the search for life, preferably with human-level intelligence. Planetary rovers would be true human surrogates capable of sophisticated decision-making to enhance their scientific productivity. We explore several key aspects of this capability: (i) visual texture analysis of rocks to enable their geological classification and so, astrobiological potential; (ii) serendipitous target acquisition whilst on the move; (iii) continuous extraction of regolith properties, including water ice whilst on the move; and (iv) deep learning-capable Bayesian net expert systems. Individually, these capabilities will provide enhanced scientific return for astrobiology missions, but together, they will provide full autonomous science capability.

Research on Human Embryos and Reproductive Materials: Revisiting Canadian Law and Policy

PubMed Central

Zarzeczny, Amy; Baltz, Jay; Bedford, Patrick; Du, Jenny; Hyun, Insoo; Jaafar, Yasmeen; Jurisicova, Andrea; Kleiderman, Erika; Koukio, Yonida; Knoppers, Bartha Maria; Leader, Arthur; Master, Zubin; Nguyen, Minh Thu; Noohi, Forough; Ravitsky, Vardit; Toews, Maeghan

2018-01-01

Research involving human embryos and reproductive materials, including certain forms of stem cell and genetic research, is a fast-moving area of science with demonstrated clinical relevance. Canada's current governance framework for this field of research urgently requires review and reconsideration in view of emerging applications. Based on a workshop involving ethics, legal, policy, scientific and clinical experts, we present a series of recommendations with the goal of informing and supporting health policy and decision-making regarding the governance of the field. With a pragmatic and principled governance approach, Canada can continue its global leadership in this field, as well as advance the long-term health and well-being of Canadians. PMID:29595433

FIGENIX: Intelligent automation of genomic annotation: expertise integration in a new software platform

PubMed Central

Gouret, Philippe; Vitiello, Vérane; Balandraud, Nathalie; Gilles, André; Pontarotti, Pierre; Danchin, Etienne GJ

2005-01-01

Background Two of the main objectives of the genomic and post-genomic era are to structurally and functionally annotate genomes which consists of detecting genes' position and structure, and inferring their function (as well as of other features of genomes). Structural and functional annotation both require the complex chaining of numerous different software, algorithms and methods under the supervision of a biologist. The automation of these pipelines is necessary to manage huge amounts of data released by sequencing projects. Several pipelines already automate some of these complex chaining but still necessitate an important contribution of biologists for supervising and controlling the results at various steps. Results Here we propose an innovative automated platform, FIGENIX, which includes an expert system capable to substitute to human expertise at several key steps. FIGENIX currently automates complex pipelines of structural and functional annotation under the supervision of the expert system (which allows for example to make key decisions, check intermediate results or refine the dataset). The quality of the results produced by FIGENIX is comparable to those obtained by expert biologists with a drastic gain in terms of time costs and avoidance of errors due to the human manipulation of data. Conclusion The core engine and expert system of the FIGENIX platform currently handle complex annotation processes of broad interest for the genomic community. They could be easily adapted to new, or more specialized pipelines, such as for example the annotation of miRNAs, the classification of complex multigenic families, annotation of regulatory elements and other genomic features of interest. PMID:16083500

Cornell Mixing Zone Expert System

EPA Pesticide Factsheets

This page provides an overview Cornell Mixing Zone Expert System water quality modeling and decision support system designed for environmental impact assessment of mixing zones resulting from wastewater discharge from point sources

Risk manager formula for success: Influencing decision making.

PubMed

Midgley, Mike

2017-10-01

Providing the ultimate decision makers with a quantitative risk analysis based on thoughtful assessment by the organization's experts enables an efficient decision. © 2017 American Society for Healthcare Risk Management of the American Hospital Association.

The mad cow problem in the UK: risk perceptions, risk management, and health policy development.

PubMed

Lanska, D J

1998-01-01

Mad cow disease or bovine spongiform encephalopathy (BSE) is a fatal neurological disease of cattle first recognized in the United Kingdom (UK) in 1986. Until recently, the UK government considered the chance of a human becoming infected with the BSE agent to be extremely remote. As a result of new developments, alarmist media attention, bureaucratic mishandling of the issues, scientific uncertainty, bickering among technical experts, and a dearth of easily assimilated and balanced information on the problem, widespread fears that affected cattle could enter the human food supply and transmit the disease to humans have periodically erupted, causing social, economic, and political consequences of tremendous magnitude. Better management of the mad cow problem could have minimized the magnitude of the epidemic among cattle, the risk to humans, and the public outrage. Trust in the British government was seriously eroded, an entire industry crippled, and international relations severely tried. Although the scientific data concerning BSE and its transmissibility to humans are still not conclusive, a growing body of (still largely circumstantial) evidence suggests that BSE may be transmissible to humans. Unfortunately, policy decisions cannot wait for a final scientific answer. Therefore, high-stakes decisions must be made in the face of this uncertainty. Such decisions should be made with the primary purpose of protecting the public, and not preferentially the economics of an industry, political alliances, or other considerations. Given that the risk to humans from BSE was (and still is) unknown and may be high, and that the perceived risk among the British public was (and still is) extraordinarily high, policies should support more aggressive interventions. Of necessity, such interventions will be preventive, as there is presently no available treatment. Such policies should be modified as necessary as the developing scientific data warrants.

Expert communities and interest-formation in the Brazilian AIDS program.

PubMed

Lago, Regina Ferro do; Costa, Nilson do Rosário

2017-05-01

This paper examines the role of the Technical Advisory Committee for antiretroviral therapy of the Brazilian AIDS program in mediating the decision-making process of including new antiretroviral (ARV) drugs in the Unified Health System services by the end of the 2000s. We conducted documental analysis and interviews with key informants from the governmental sphere and professionals. The work features the Technical Advisory Committee as an "expert community", defined as a network of individuals with expertise and competence in a particular sphere and whose knowledge is relevant in critical public policy decision areas. It also indicates that the decision-making process for inclusion of antiretroviral drugs in the Brazilian program was incremental, considering the expectations of the innovative leader companies of pharmaceutical market. The work describes thus the results of the interaction of government interests, pharmaceutical industry and experts in the implementation of a relevant international policy. It provides arguments and evidence for understanding the role of expert communities on a sectorial public policy so far analyzed predominantly from the perspective of social movements.

Evidence of different underlying processes in pattern recall and decision-making.

PubMed

Gorman, Adam D; Abernethy, Bruce; Farrow, Damian

2015-01-01

The visual search characteristics of expert and novice basketball players were recorded during pattern recall and decision-making tasks to determine whether the two tasks shared common visual-perceptual processing strategies. The order in which participants entered the pattern elements in the recall task was also analysed to further examine the nature of the visual-perceptual strategies and the relative emphasis placed upon particular pattern features. The experts demonstrated superior performance across the recall and decision-making tasks [see also Gorman, A. D., Abernethy, B., & Farrow, D. (2012). Classical pattern recall tests and the prospective nature of expert performance. The Quarterly Journal of Experimental Psychology, 65, 1151-1160; Gorman, A. D., Abernethy, B., & Farrow, D. (2013a). Is the relationship between pattern recall and decision-making influenced by anticipatory recall? The Quarterly Journal of Experimental Psychology, 66, 2219-2236)] but a number of significant differences in the visual search data highlighted disparities in the processing strategies, suggesting that recall skill may utilize different underlying visual-perceptual processes than those required for accurate decision-making performance in the natural setting. Performance on the recall task was characterized by a proximal-to-distal order of entry of the pattern elements with participants tending to enter the players located closest to the ball carrier earlier than those located more distal to the ball carrier. The results provide further evidence of the underlying perceptual processes employed by experts when extracting visual information from complex and dynamic patterns.

Standing in Your Peer’s Shoes Hurts Your Feats: The Self-Others Discrepancy in Risk Attitude and Impulsivity

PubMed Central

Białaszek, Wojciech; Bakun, Piotr; McGoun, Elton; Zielonka, Piotr

2016-01-01

It is often a good strategy to “stand in the other person’s shoes” to see a situation from a different perspective. People frequently attempt to infer what someone else would recommend when no advisor is available to help with a decision. Such situations commonly concern intertemporal or risky choices, and the usual assumption is that lay people make such decisions differently than experts do. The aim of our study was to determine what intertemporal and risky decisions people make when they take their own perspective, the perspective of a peer, and the perspectives of an expert or an entrepreneur. In a series of three experiments using a between-subject design, we found that taking the peer’s perspective made participants behave more impulsively and more risk aversely in relation to the participants’ own perspectives and in relation to their perceptions of experts and entrepreneurs perspectives. Taking an expert’s or an entrepreneur’s perspective did not change participants’ own intertemporal and risky decisions. We explain the findings using the risk as value and the lesser mind theories. Imagining the opponent’s perspective in a negotiation as one is advised to do might inadvertently lead to problems because we always see her as more impulsive and more risk averse than she really is. This means that taking a perspective of an expert – not a peer – would be a good way to predict what decisions our opponents make. PMID:26925015

Using immersive simulation for training first responders for mass casualty incidents.

PubMed

Wilkerson, William; Avstreih, Dan; Gruppen, Larry; Beier, Klaus-Peter; Woolliscroft, James

2008-11-01

A descriptive study was performed to better understand the possible utility of immersive virtual reality simulation for training first responders in a mass casualty event. Utilizing a virtual reality cave automatic virtual environment (CAVE) and high-fidelity human patient simulator (HPS), a group of experts modeled a football stadium that experienced a terrorist explosion during a football game. Avatars (virtual patients) were developed by expert consensus that demonstrated a spectrum of injuries ranging from death to minor lacerations. A group of paramedics was assessed by observation for decisions made and action taken. A critical action checklist was created and used for direct observation and viewing videotaped recordings. Of the 12 participants, only 35.7% identified the type of incident they encountered. None identified a secondary device that was easily visible. All participants were enthusiastic about the simulation and provided valuable comments and insights. Learner feedback and expert performance review suggests that immersive training in a virtual environment has the potential to be a powerful tool to train first responders for high-acuity, low-frequency events, such as a terrorist attack.

Accident diagnosis system based on real-time decision tree expert system

NASA Astrophysics Data System (ADS)

Nicolau, Andressa dos S.; Augusto, João P. da S. C.; Schirru, Roberto

2017-06-01

Safety is one of the most studied topics when referring to power stations. For that reason, sensors and alarms develop an important role in environmental and human protection. When abnormal event happens, it triggers a chain of alarms that must be, somehow, checked by the control room operators. In this case, diagnosis support system can help operators to accurately identify the possible root-cause of the problem in short time. In this article, we present a computational model of a generic diagnose support system based on artificial intelligence, that was applied on the dataset of two real power stations: Angra1 Nuclear Power Plant and Santo Antônio Hydroelectric Plant. The proposed system processes all the information logged in the sequence of events before a shutdown signal using the expert's knowledge inputted into an expert system indicating the chain of events, from the shutdown signal to its root-cause. The results of both applications showed that the support system is a potential tool to help the control room operators identify abnormal events, as accidents and consequently increase the safety.

Expert elicitation of population-level effects of disturbance

USGS Publications Warehouse

Fleishman, Erica; Burgman, Mark; Runge, Michael C.; Schick, Robert S; Krauss, Scott; Popper, Arthur N.; Hawkins, Anthony

2016-01-01

Expert elicitation is a rigorous method for synthesizing expert knowledge to inform decision making and is reliable and practical when field data are limited. We evaluated the feasibility of applying expert elicitation to estimate population-level effects of disturbance on marine mammals. Diverse experts estimated parameters related to mortality and sublethal injury of North Atlantic right whales (Eubalaena glacialis). We are now eliciting expert knowledge on the movement of right whales among geographic regions to parameterize a spatial model of health. Expert elicitation complements methods such as simulation models or extrapolations from other species, sometimes with greater accuracy and less uncertainty.

Intelligent monitoring of critical pathological events during anesthesia.

PubMed

Gohil, Bhupendra; Gholamhhosseini, Hamid; Harrison, Michael J; Lowe, Andrew; Al-Jumaily, Ahmed

2007-01-01

Expert algorithms in the field of intelligent patient monitoring have rapidly revolutionized patient care thereby improving patient safety. Patient monitoring during anesthesia requires cautious attention by anesthetists who are monitoring many modalities, diagnosing clinically critical events and performing patient management tasks simultaneously. The mishaps that occur during day-to-day anesthesia causing disastrous errors in anesthesia administration were classified and studied by Reason [1]. Human errors in anesthesia account for 82% of the preventable mishaps [2]. The aim of this paper is to develop a clinically useful diagnostic alarm system for detecting critical events during anesthesia administration. The development of an expert diagnostic alarm system called ;RT-SAAM' for detecting critical pathological events in the operating theatre is presented. This system provides decision support to the anesthetist by presenting the diagnostic results on an integrative, ergonomic display and thus enhancing patient safety. The performance of the system was validated through a series of offline and real-time testing in the operation theatre. When detecting absolute hypovolaemia (AHV), moderate level of agreement was observed between RT-SAAM and the human expert (anesthetist) during surgical procedures. RT-SAAM is a clinically useful diagnostic tool which can be easily modified for diagnosing additional critical pathological events like relative hypovolaemia, fall in cardiac output, sympathetic response and malignant hyperpyrexia during surgical procedures. RT-SAAM is currently being tested at the Auckland City Hospital with ethical approval from the local ethics committees.

A method to harness global crowd-sourced data to understand travel behavior in avalanche terrain.

NASA Astrophysics Data System (ADS)

Hendrikx, J.; Johnson, J.

2015-12-01

To date, most studies of the human dimensions of decision making in avalanche terrain has focused on two areas - post-accident analysis using accident reports/interviews and, the development of tools as decision forcing aids. We present an alternate method using crowd-sourced citizen science, for understanding decision-making in avalanche terrain. Our project combines real-time GPS tracking via a smartphone application, with internet based surveys of winter backcountry users as a method to describe and quantify travel practices in concert with group decision-making dynamics, and demographic data of participants during excursions. Effectively, we use the recorded GPS track taken within the landscape as an expression of the decision making processes and terrain usage by the group. Preliminary data analysis shows that individual experience levels, gender, avalanche hazard, and group composition all influence the ways in which people travel in avalanche terrain. Our results provide the first analysis of coupled real-time GPS tracking of the crowd while moving in avalanche terrain combined with psychographic and demographic correlates. This research will lead to an improved understanding of real-time decision making in avalanche terrain. In this paper we will specifically focus on the presentation of the methods used to solicit, and then harness the crowd to obtain data in a unique and innovative application of citizen science where the movements within the terrain are the desired output data (Figure 1). Figure 1: Example GPS tracks sourced from backcountry winter users in the Teton Pass area (Wyoming), from the 2014-15 winter season, where tracks in red represent those recorded as self-assessed experts (as per our survey), and where tracks in blue represent those recorded as self-assessed intermediates. All tracks shown were obtained under similar avalanche conditions. Statistical analysis of terrain metrics showed that the experts used steeper terrain than the intermediate users under similar avalanche conditions, demonstrating different terrain choice and use as a function of experience rather than hazard level.

Active Learning with Irrelevant Examples

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; Mazzoni, Dominic

2009-01-01

An improved active learning method has been devised for training data classifiers. One example of a data classifier is the algorithm used by the United States Postal Service since the 1960s to recognize scans of handwritten digits for processing zip codes. Active learning algorithms enable rapid training with minimal investment of time on the part of human experts to provide training examples consisting of correctly classified (labeled) input data. They function by identifying which examples would be most profitable for a human expert to label. The goal is to maximize classifier accuracy while minimizing the number of examples the expert must label. Although there are several well-established methods for active learning, they may not operate well when irrelevant examples are present in the data set. That is, they may select an item for labeling that the expert simply cannot assign to any of the valid classes. In the context of classifying handwritten digits, the irrelevant items may include stray marks, smudges, and mis-scans. Querying the expert about these items results in wasted time or erroneous labels, if the expert is forced to assign the item to one of the valid classes. In contrast, the new algorithm provides a specific mechanism for avoiding querying the irrelevant items. This algorithm has two components: an active learner (which could be a conventional active learning algorithm) and a relevance classifier. The combination of these components yields a method, denoted Relevance Bias, that enables the active learner to avoid querying irrelevant data so as to increase its learning rate and efficiency when irrelevant items are present. The algorithm collects irrelevant data in a set of rejected examples, then trains the relevance classifier to distinguish between labeled (relevant) training examples and the rejected ones. The active learner combines its ranking of the items with the probability that they are relevant to yield a final decision about which item to present to the expert for labeling. Experiments on several data sets have demonstrated that the Relevance Bias approach significantly decreases the number of irrelevant items queried and also accelerates learning speed.

Rhetorical Consequences of the Computer Society: Expert Systems and Human Communication.

ERIC Educational Resources Information Center

Skopec, Eric Wm.

Expert systems are computer programs that solve selected problems by modelling domain-specific behaviors of human experts. These computer programs typically consist of an input/output system that feeds data into the computer and retrieves advice, an inference system using the reasoning and heuristic processes of human experts, and a knowledge…

a Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

NASA Astrophysics Data System (ADS)

Park, Young-Tack; Kim, Jae-Hoon; Park, Hyun-Soo

1997-06-01

Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

Experts in offside decision making learn to compensate for their illusory perceptions.

PubMed

Put, Koen; Baldo M, V C; Cravo, André M; Wagemans, Johan; Helsen, Werner F

2013-12-01

In association football, the flash-lag effect appears to be a viable explanation for erroneous offside decision making. Due to this spatiotemporal illusion, assistant referees (ARs) perceive the player who receives the ball ahead of his real position. In this experiment, a laboratory decision-making task was used to demonstrate that international top-class ARs, compared with amateur soccer players, do not have superior perceptual sensitivity. They clearly modify their decision criterion according to the contextual needs and, therefore, show a higher response bias toward not responding to the stimulus, in particular in the most difficult situations. Thus, international ARs show evidence for response-level compensation, resulting in a specific cost (i.e., more misses), which clearly reflects the use of particular (cognitive) strategies. In summary, it appears that experts in offside decision making can be distinguished from novices more on the cognitive or decision-making level than on the perceptual level.

[A model for shared decision-making with frail older patients: consensus reached using Delphi technique].

PubMed

van de Pol, M H J; Fluit, C R M G; Lagro, J; Lagro-Janssen, A L M; Olde Rikkert, M G M

2017-01-01

To develop a model for shared decision-making with frail older patients. Online Delphi forum. We used a three-round Delphi technique to reach consensus on the structure of a model for shared decision-making with older patients. The expert panel consisted of 16 patients (round 1), and 59 professionals (rounds 1-3). In round 1, the panel of experts was asked about important steps in the process of shared decision-making and the draft model was introduced. Rounds 2 and 3 were used to adapt the model and test it for 'importance' and 'feasibility'. Consensus for the dynamic shared decision-making model as a whole was achieved for both importance (91% panel agreement) and feasibility (76% panel agreement). Shared decision-making with older patients is a dynamic process. It requires a continuous supportive dialogue between health care professional and patient.

Ontology based decision system for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Trabelsi Ben Ameur, Soumaya; Cloppet, Florence; Wendling, Laurent; Sellami, Dorra

2018-04-01

In this paper, we focus on analysis and diagnosis of breast masses inspired by expert concepts and rules. Accordingly, a Bag of Words is built based on the ontology of breast cancer diagnosis, accurately described in the Breast Imaging Reporting and Data System. To fill the gap between low level knowledge and expert concepts, a semantic annotation is developed using a machine learning tool. Then, breast masses are classified into benign or malignant according to expert rules implicitly modeled with a set of classifiers (KNN, ANN, SVM and Decision Tree). This semantic context of analysis offers a frame where we can include external factors and other meta-knowledge such as patient risk factors as well as exploiting more than one modality. Based on MRI and DECEDM modalities, our developed system leads a recognition rate of 99.7% with Decision Tree where an improvement of 24.7 % is obtained owing to semantic analysis.

Mining balance disorders' data for the development of diagnostic decision support systems.

PubMed

Exarchos, T P; Rigas, G; Bibas, A; Kikidis, D; Nikitas, C; Wuyts, F L; Ihtijarevic, B; Maes, L; Cenciarini, M; Maurer, C; Macdonald, N; Bamiou, D-E; Luxon, L; Prasinos, M; Spanoudakis, G; Koutsouris, D D; Fotiadis, D I

2016-10-01

In this work we present the methodology for the development of the EMBalance diagnostic Decision Support System (DSS) for balance disorders. Medical data from patients with balance disorders have been analysed using data mining techniques for the development of the diagnostic DSS. The proposed methodology uses various data, ranging from demographic characteristics to clinical examination, auditory and vestibular tests, in order to provide an accurate diagnosis. The system aims to provide decision support for general practitioners (GPs) and experts in the diagnosis of balance disorders as well as to provide recommendations for the appropriate information and data to be requested at each step of the diagnostic process. Detailed results are provided for the diagnosis of 12 balance disorders, both for GPs and experts. Overall, the reported accuracy ranges from 59.3 to 89.8% for GPs and from 74.3 to 92.1% for experts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bridging the Gap between Experts in Designing Multimedia-Based Instructional Media for Learning

ERIC Educational Resources Information Center

Razak, Rafiza Abdul

2013-01-01

The research identified and explored the cognitive knowledge among the instructional multimedia design and development experts comprising of multimedia designer, graphic designer, subject-matter expert and instructional designer. A critical need exists for a solid understanding of the factors that influence team decision making and performance in…

Implementation of an Expert System for Instructional Design: Phase 2. Design Document & Technical Report.

ERIC Educational Resources Information Center

Merrill, M. David; Li, Zhongmin

The purpose of this project was to develop a prototype expert instructional design system (ID Expert) which would demonstrate the feasibility of a consultation system for use by inexperienced instructional designers. The prototype gathers information from the designer and then makes recommendations for instructional design decisions. The output of…

Dog experts' brains distinguish socially relevant body postures similarly in dogs and humans.

PubMed

Kujala, Miiamaaria V; Kujala, Jan; Carlson, Synnöve; Hari, Riitta

2012-01-01

We read conspecifics' social cues effortlessly, but little is known about our abilities to understand social gestures of other species. To investigate the neural underpinnings of such skills, we used functional magnetic resonance imaging to study the brain activity of experts and non-experts of dog behavior while they observed humans or dogs either interacting with, or facing away from a conspecific. The posterior superior temporal sulcus (pSTS) of both subject groups dissociated humans facing toward each other from humans facing away, and in dog experts, a distinction also occurred for dogs facing toward vs. away in a bilateral area extending from the pSTS to the inferior temporo-occipital cortex: the dissociation of dog behavior was significantly stronger in expert than control group. Furthermore, the control group had stronger pSTS responses to humans than dogs facing toward a conspecific, whereas in dog experts, the responses were of similar magnitude. These findings suggest that dog experts' brains distinguish socially relevant body postures similarly in dogs and humans.

Eliciting expert opinion for economic models: an applied example.

PubMed

Leal, José; Wordsworth, Sarah; Legood, Rosa; Blair, Edward

2007-01-01

Expert opinion is considered as a legitimate source of information for decision-analytic modeling where required data are unavailable. Our objective was to develop a practical computer-based tool for eliciting expert opinion about the shape of the uncertainty distribution around individual model parameters. We first developed a prepilot survey with departmental colleagues to test a number of alternative approaches to eliciting opinions on the shape of the uncertainty distribution around individual parameters. This information was used to develop a survey instrument for an applied clinical example. This involved eliciting opinions from experts to inform a number of parameters involving Bernoulli processes in an economic model evaluating DNA testing for families with a genetic disease, hypertrophic cardiomyopathy. The experts were cardiologists, clinical geneticists, and laboratory scientists working with cardiomyopathy patient populations and DNA testing. Our initial prepilot work suggested that the more complex elicitation techniques advocated in the literature were difficult to use in practice. In contrast, our approach achieved a reasonable response rate (50%), provided logical answers, and was generally rated as easy to use by respondents. The computer software user interface permitted graphical feedback throughout the elicitation process. The distributions obtained were incorporated into the model, enabling the use of probabilistic sensitivity analysis. There is clearly a gap in the literature between theoretical elicitation techniques and tools that can be used in applied decision-analytic models. The results of this methodological study are potentially valuable for other decision analysts deriving expert opinion.

Regulatory decision-making under uncertainty: are costs proportionate to benefits when restricting dangerous chemicals on European markets?

PubMed

Brouwer, Roy; Cauchi, Jonathan; Verhoeven, Julia

2014-04-01

Since 2007 regulation 1907/2006/EC concerning the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) is in force in Europe to reduce the adverse effects of hazardous chemical substances on human health and the environment. Implementation of the regulation by the European Chemicals Agency (ECHA) is supported by a Socio-Economic Analysis (SEA) Committee, consisting of European experts who help prepare ECHA's opinion on proposals for either restricting or authorizing dangerous substances. This paper presents the outcomes of the SEA underlying the first restriction proposals. Member states proposing a restriction have to show that it will reduce the risks to an acceptable level at a cost which is proportionate to the avoided risk. What is considered proportionate is not clearly defined in REACH. The opinion making process is characterized by many uncertainties: the expert group had no previous experiences to fall back on and limited information about the expected costs and benefits of the proposed restrictions. The study provides insight into expert opinions on environmental and health risks under uncertainty in the specific context of REACH. Particular attention is paid to the confidence experts place on the estimated socio-economic benefits of the avoided risks compared to the estimated compliance costs. Copyright © 2014 Elsevier Inc. All rights reserved.

Individual versus group decision making: Jurors’ reliance on central and peripheral information to evaluate expert testimony

PubMed Central

Bottoms, Bette L.; Peter-Hagene, Liana C.

2017-01-01

To investigate dual-process persuasion theories in the context of group decision making, we studied low and high need-for-cognition (NFC) participants within a mock trial study. Participants considered plaintiff and defense expert scientific testimony that varied in argument strength. All participants heard a cross-examination of the experts focusing on peripheral information (e.g., credentials) about the expert, but half were randomly assigned to also hear central information highlighting flaws in the expert’s message (e.g., quality of the research presented by the expert). Participants rendered pre- and post-group-deliberation verdicts, which were considered “scientifically accurate” if the verdicts reflected the strong (versus weak) expert message, and “scientifically inaccurate” if they reflected the weak (versus strong) expert message. For individual participants, we replicated studies testing classic persuasion theories: Factors promoting reliance on central information (i.e., central cross-examination, high NFC) improved verdict accuracy because they sensitized individual participants to the quality discrepancy between the experts’ messages. Interestingly, however, at the group level, the more that scientifically accurate mock jurors discussed peripheral (versus central) information about the experts, the more likely their group was to reach the scientifically accurate verdict. When participants were arguing for the scientifically accurate verdict consistent with the strong expert message, peripheral comments increased their persuasiveness, which made the group more likely to reach the more scientifically accurate verdict. PMID:28931011

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

PubMed

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

PubMed Central

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

Good Thinking or Gut Feeling? Cognitive Reflection and Intuition in Traders, Bankers and Financial Non-Experts

PubMed Central

Thoma, Volker; White, Elliott; Panigrahi, Asha; Strowger, Vanessa; Anderson, Irina

2015-01-01

The current study investigated differences in decision-making style and risk-taking between financial traders, non-trading bank employees, and people not working in finance. Traders scored significantly higher than participants in the other two groups on the cognitive reflection test (CRT) which measures the tendency to inhibit automatic but frequently false responses in reasoning tasks. Scores for traders compared to people outside the banking sector were also higher on a self-rated scale for reflective thinking in decision-making, but there were no differences in self-rated intuitive thinking between groups. Financial risk-taking correlated with cognitive reflection scores and was significantly lower in the non-expert group compared to the other groups working in financial services. Traders in the current study showed no elevated preference to use ‘intuition’ in their decision-making compared to other groups. Overall, these results indicate that compared to non-expert participants financial traders have a higher self-rated tendency for reflective thinking and a greater propensity to inhibit the use of mental shortcuts (heuristics) in decision-making. PMID:25875674

Confessions and expert testimony.

PubMed

Weiss, Kenneth J

2003-01-01

In this clinical paper, the author discusses criminal confessions from the point of view of the expert witness who may be asked to comment on the reliability of the statement and waiver of rights. From the time a suspect is in police custody, constitutional protections against self-incrimination and for due process are in place. The Supreme Court set the standard for these situations in the 1966 Miranda v. Arizona decision. Although it has long been criticized by law enforcement, the decision was upheld in the 2000 decision in Dickerson v. U.S. For a waiver of rights to be valid, it must be a knowing, intelligent, and voluntary decision. Voluntariness is an equation of objective and subjective variables. Treatment by police, physical conditions of interrogation, the suspect's experience and mental state can alter the reliability of a confession. Accordingly, the author has devised a mnemonic for the recognition of conditions that may give rise to expert testimony. The conditions are: Mental illness, Intoxication, Retardation, Acquiescence, Narcotic withdrawal, Deception, and Abuse. These are discussed, supported by examples from the author's practice.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Non-pharmaceutical public health interventions for pandemic influenza: an evaluation of the evidence base.

PubMed

Aledort, Julia E; Lurie, Nicole; Wasserman, Jeffrey; Bozzette, Samuel A

2007-08-15

In an influenza pandemic, the benefit of vaccines and antiviral medications will be constrained by limitations on supplies and effectiveness. Non-pharmaceutical public health interventions will therefore be vital in curtailing disease spread. However, the most comprehensive assessments of the literature to date recognize the generally poor quality of evidence on which to base non-pharmaceutical pandemic planning decisions. In light of the need to prepare for a possible pandemic despite concerns about the poor quality of the literature, combining available evidence with expert opinion about the relative merits of non-pharmaceutical interventions for pandemic influenza may lead to a more informed and widely accepted set of recommendations. We evaluated the evidence base for non-pharmaceutical public health interventions. Then, based on the collective evidence, we identified a set of recommendations for and against interventions that are specific to both the setting in which an intervention may be used and the pandemic phase, and which can be used by policymakers to prepare for a pandemic until scientific evidence can definitively respond to planners' needs. Building on reviews of past pandemics and recent historical inquiries, we evaluated the relative merits of non-pharmaceutical interventions by combining available evidence from the literature with qualitative and quantitative expert opinion. Specifically, we reviewed the recent scientific literature regarding the prevention of human-to-human transmission of pandemic influenza, convened a meeting of experts from multiple disciplines, and elicited expert recommendation about the use of non-pharmaceutical public health interventions in a variety of settings (healthcare facilities; community-based institutions; private households) and pandemic phases (no pandemic; no US pandemic; early localized US pandemic; advanced US pandemic). The literature contained a dearth of evidence on the efficacy or effectiveness of most non-pharmaceutical interventions for influenza. In an effort to inform decision-making in the absence of strong scientific evidence, the experts ultimately endorsed hand hygiene and respiratory etiquette, surveillance and case reporting, and rapid viral diagnosis in all settings and during all pandemic phases. They also encouraged patient and provider use of masks and other personal protective equipment as well as voluntary self-isolation of patients during all pandemic phases. Other non-pharmaceutical interventions including mask-use and other personal protective equipment for the general public, school and workplace closures early in an epidemic, and mandatory travel restrictions were rejected as likely to be ineffective, infeasible, or unacceptable to the public. The demand for scientific evidence on non-pharmaceutical public health interventions for influenza is pervasive, and present policy recommendations must rely heavily on expert judgment. In the absence of a definitive science base, our assessment of the evidence identified areas for further investigation as well as non-pharmaceutical public health interventions that experts believe are likely to be beneficial, feasible and widely acceptable in an influenza pandemic.

The Many Faces of a Software Engineer in a Research Community

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marinovici, Maria C.; Kirkham, Harold

2013-10-14

The ability to gather, analyze and make decisions based on real world data is changing nearly every field of human endeavor. These changes are particularly challenging for software engineers working in a scientific community, designing and developing large, complex systems. To avoid the creation of a communications gap (almost a language barrier), the software engineers should possess an ‘adaptive’ skill. In the science and engineering research community, the software engineers must be responsible for more than creating mechanisms for storing and analyzing data. They must also develop a fundamental scientific and engineering understanding of the data. This paper looks atmore » the many faces that a software engineer should have: developer, domain expert, business analyst, security expert, project manager, tester, user experience professional, etc. Observations made during work on a power-systems scientific software development are analyzed and extended to describe more generic software development projects.« less

A Review on the Bioinformatics Tools for Neuroimaging

PubMed Central

MAN, Mei Yen; ONG, Mei Sin; Mohamad, Mohd Saberi; DERIS, Safaai; SULONG, Ghazali; YUNUS, Jasmy; CHE HARUN, Fauzan Khairi

2015-01-01

Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system. PMID:27006633

Automatic Sleep Stage Determination by Multi-Valued Decision Making Based on Conditional Probability with Optimal Parameters

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Wang, Xingyu; Nakamura, Masatoshi

Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determination techniques to be applied for clinical practice. The aim of this study is to develop an automatic sleep stage determination system which is optimized for variable sleep data. The main methodology includes two modules: expert knowledge database construction and automatic sleep stage determination. Visual inspection by a qualified clinician is utilized to obtain the probability density function of parameters during the learning process of expert knowledge database construction. Parameter selection is introduced in order to make the algorithm flexible. Automatic sleep stage determination is manipulated based on conditional probability. The result showed close agreement comparing with the visual inspection by clinician. The developed system can meet the customized requirements in hospitals and institutions.

Sinecatechins and imiquimod as proactive sequential therapy of external genital and perianal warts in adults.

PubMed

Schöfer, Helmut; Tatti, Silvio; Lynde, Charles W; Skerlev, Mihael; Hercogová, Jana; Rotaru, Maria; Ballesteros, Juan; Calzavara-Pinton, Piergiacomo

2017-12-01

This review about the proactive sequential therapy (PST) of external genital and perianal warts (EGW) is based on the most current available clinical literature and on the broad clinical experience of a group of international experts, physicians who are well versed in the treatment of human papillomavirus-associated diseases. It provides a practical guide for the treatment of EGW, including epidemiology, etiology, clinical appearance, and diagnostic procedures for these viral infections. Furthermore, the treatment goals and current treatment options, elucidating provider- and patient-applied therapies, and the parameters driving treatment decisions are summarized. Specifically, the mode of action of the topical treatments sinecatechins and imiquimod, as well as the PST for EGW to achieve rapid and sustained clearance is discussed. The group of experts has developed a treatment algorithm giving healthcare providers a practical tool for the treatment of EGW which is very valuable in the presence of many different treatment options.

Processes in construction of failure management expert systems from device design information

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Lance, Nick

1987-01-01

This paper analyzes the tasks and problem solving methods used by an engineer in constructing a failure management expert system from design information about the device to te diagnosed. An expert test engineer developed a trouble-shooting expert system based on device design information and experience with similar devices, rather than on specific expert knowledge gained from operating the device or troubleshooting its failures. The construction of the expert system was intensively observed and analyzed. This paper characterizes the knowledge, tasks, methods, and design decisions involved in constructing this type of expert system, and makes recommendations concerning tools for aiding and automating construction of such systems.

Perspective on intelligent avionics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, H.L.

1987-01-01

Technical issues which could potentially limit the capability and acceptibility of expert systems decision-making for avionics applications are addressed. These issues are: real-time AI, mission-critical software, conventional algorithms, pilot interface, knowledge acquisition, and distributed expert systems. Examples from on-going expert system development programs are presented to illustrate likely architectures and applications of future intelligent avionic systems. 13 references.

Students' Refinement of Knowledge during the Development of Knowledge Bases for Expert Systems.

ERIC Educational Resources Information Center

Lippert, Renate; Finley, Fred

The refinement of the cognitive knowledge base was studied through exploration of the transition from novice to expert and the use of an instructional strategy called novice knowledge engineering. Six college freshmen, who were enrolled in an honors physics course, used an expert system to create questions, decisions, rules, and explanations…

Impact of advanced monitoring variables on intraoperative clinical decision-making: an international survey.

PubMed

Joosten, Alexandre; Desebbe, Olivier; Suehiro, Koichi; Essiet, Mfonobong; Alexander, Brenton; Ricks, Cameron; Rinehart, Joseph; Faraoni, David; Cecconi, Maurizio; Van der Linden, Philippe; Cannesson, Maxime

2017-02-01

To assess the relationship between the addition of advanced monitoring variables and changes in clinical decision-making. A 15-questions survey was anonymously emailed to international experts and physician members of five anesthesia societies which focused on assessing treatment decisions of clinicians during three realistic clinical scenarios measured at two distinct time points. The first is when typical case information and basic monitoring (T1) were provided, and then once again after the addition of advanced monitoring variables (T2). We hypothesized that the addition of advanced variables would increase the incidence of an optimal therapeutic decision (a priori defined as the answer with the highest percentage of expert agreement) and decrease the variability among the physician's suggested treatments. The survey was completed by 18 experts and 839 physicians. Overall, adding advanced monitoring did not significantly increase physician response accuracy, with the least substantial changes noted on questions related to volume expansion or vasopressor administration. Moreover, advanced monitoring data did not significantly decrease the high level of initial practice variability in physician suggested treatments (P = 0.13), in contrast to the low variability observed within the expert group (P = 0.039). Additionally, 5-10 years of practice (P < 0.0001) and a cardiovascular subspecialty (P = 0.048) were both physician characteristics associated with a higher rate of optimal therapeutic decisions. The addition of advanced variables was of limited benefit for most physicians, further indicating the need for more in depth education on the clinical value and technical understanding of such variables.

Fuzzy MCDM Technique for Planning the Environment Watershed

NASA Astrophysics Data System (ADS)

Chen, Yi-Chun; Lien, Hui-Pang; Tzeng, Gwo-Hshiung; Yang, Lung-Shih; Yen, Leon

In the real word, the decision making problems are very vague and uncertain in a number of ways. The most criteria have interdependent and interactive features so they cannot be evaluated by conventional measures method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environmentwatershed. The Fuzzy Analytic Hierarchy Process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception. A questionnaire was used to find out from three related groups comprising fifteen experts. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. Incorporated the decision makers’ attitude towards preference, overall performance value of each alternative can be obtained based on the concept of Fuzzy Multiple Criteria Decision Making (FMCDM). This research also gives an example of evaluating consisting of five alternatives, solicited from a environmentwatershed plan works in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach.

Assessing what to address in science communication.

PubMed

Bruine de Bruin, Wändi; Bostrom, Ann

2013-08-20

As members of a democratic society, individuals face complex decisions about whether to support climate change mitigation, vaccinations, genetically modified food, nanotechnology, geoengineering, and so on. To inform people's decisions and public debate, scientific experts at government agencies, nongovernmental organizations, and other organizations aim to provide understandable and scientifically accurate communication materials. Such communications aim to improve people's understanding of the decision-relevant issues, and if needed, promote behavior change. Unfortunately, existing communications sometimes fail when scientific experts lack information about what people need to know to make more informed decisions or what wording people use to describe relevant concepts. We provide an introduction for scientific experts about how to use mental models research with intended audience members to inform their communication efforts. Specifically, we describe how to conduct interviews to characterize people's decision-relevant beliefs or mental models of the topic under consideration, identify gaps and misconceptions in their knowledge, and reveal their preferred wording. We also describe methods for designing follow-up surveys with larger samples to examine the prevalence of beliefs as well as the relationships of beliefs with behaviors. Finally, we discuss how findings from these interviews and surveys can be used to design communications that effectively address gaps and misconceptions in people's mental models in wording that they understand. We present applications to different scientific domains, showing that this approach leads to communications that improve recipients' understanding and ability to make informed decisions.

Dog Experts' Brains Distinguish Socially Relevant Body Postures Similarly in Dogs and Humans

PubMed Central

Kujala, Miiamaaria V.; Kujala, Jan; Carlson, Synnöve; Hari, Riitta

2012-01-01

We read conspecifics' social cues effortlessly, but little is known about our abilities to understand social gestures of other species. To investigate the neural underpinnings of such skills, we used functional magnetic resonance imaging to study the brain activity of experts and non-experts of dog behavior while they observed humans or dogs either interacting with, or facing away from a conspecific. The posterior superior temporal sulcus (pSTS) of both subject groups dissociated humans facing toward each other from humans facing away, and in dog experts, a distinction also occurred for dogs facing toward vs. away in a bilateral area extending from the pSTS to the inferior temporo-occipital cortex: the dissociation of dog behavior was significantly stronger in expert than control group. Furthermore, the control group had stronger pSTS responses to humans than dogs facing toward a conspecific, whereas in dog experts, the responses were of similar magnitude. These findings suggest that dog experts' brains distinguish socially relevant body postures similarly in dogs and humans. PMID:22720054

Sorting Through the Safety Data Haystack: Using Machine Learning to Identify Individual Case Safety Reports in Social-Digital Media.

PubMed

Comfort, Shaun; Perera, Sujan; Hudson, Zoe; Dorrell, Darren; Meireis, Shawman; Nagarajan, Meenakshi; Ramakrishnan, Cartic; Fine, Jennifer

2018-06-01

There is increasing interest in social digital media (SDM) as a data source for pharmacovigilance activities; however, SDM is considered a low information content data source for safety data. Given that pharmacovigilance itself operates in a high-noise, lower-validity environment without objective 'gold standards' beyond process definitions, the introduction of large volumes of SDM into the pharmacovigilance workflow has the potential to exacerbate issues with limited manual resources to perform adverse event identification and processing. Recent advances in medical informatics have resulted in methods for developing programs which can assist human experts in the detection of valid individual case safety reports (ICSRs) within SDM. In this study, we developed rule-based and machine learning (ML) models for classifying ICSRs from SDM and compared their performance with that of human pharmacovigilance experts. We used a random sampling from a collection of 311,189 SDM posts that mentioned Roche products and brands in combination with common medical and scientific terms sourced from Twitter, Tumblr, Facebook, and a spectrum of news media blogs to develop and evaluate three iterations of an automated ICSR classifier. The ICSR classifier models consisted of sub-components to annotate the relevant ICSR elements and a component to make the final decision on the validity of the ICSR. Agreement with human pharmacovigilance experts was chosen as the preferred performance metric and was evaluated by calculating the Gwet AC1 statistic (gKappa). The best performing model was tested against the Roche global pharmacovigilance expert using a blind dataset and put through a time test of the full 311,189-post dataset. During this effort, the initial strict rule-based approach to ICSR classification resulted in a model with an accuracy of 65% and a gKappa of 46%. Adding an ML-based adverse event annotator improved the accuracy to 74% and gKappa to 60%. This was further improved by the addition of an additional ML ICSR detector. On a blind test set of 2500 posts, the final model demonstrated a gKappa of 78% and an accuracy of 83%. In the time test, it took the final model 48 h to complete a task that would have taken an estimated 44,000 h for human experts to perform. The results of this study indicate that an effective and scalable solution to the challenge of ICSR detection in SDM includes a workflow using an automated ML classifier to identify likely ICSRs for further human SME review.

Evaluating the quality and use of economic data in decisions about essential medicines.

PubMed

Moucheraud, Corrina; Wirtz, Veronika J; Reich, Michael R

2015-10-01

To evaluate the quality of economic data provided in applications to the World Health Organization (WHO) Model List of Essential Medicines and to evaluate the role of these data in decision-making by the expert committee that considers the applications. We analysed applications submitted to the WHO Expert Committee on the Selection and Use of Essential Medicines between 2002 and 2013. The completeness of data on the price and cost-effectiveness of medicines was extracted from application documents and coded using a four-point scale. We recorded whether or not the expert committee discussed economic information and the outcomes of each application. Associations between the completeness of economic data and application outcomes were assessed using χ 2 tests. The expert committee received 134 applications. Only eight applications (6%) included complete price data and economic evaluation data. Many applicants omitted or misinterpreted the economic evaluation section of the application form. Despite the lack of economic data, all applications were reviewed by the committee. There was no significant association between the completeness of economic information and application outcomes. The expert committee tried to address information gaps in applications by further review and analysis of data related to the application. The World Health Organization should revise the instructions to applicants on economic data requirements; develop new mechanisms to assist applicants in completing the application process; and define methods for the use of economic data in decision-making.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Expert Knowledge Influences Decision-Making for Couples Receiving Positive Prenatal Chromosomal Microarray Testing Results.

PubMed

Rubel, M A; Werner-Lin, A; Barg, F K; Bernhardt, B A

2017-09-01

To assess how participants receiving abnormal prenatal genetic testing results seek information and understand the implications of results, 27 US female patients and 12 of their male partners receiving positive prenatal microarray testing results completed semi-structured phone interviews. These interviews documented participant experiences with chromosomal microarray testing, understanding of and emotional response to receiving results, factors affecting decision-making about testing and pregnancy termination, and psychosocial needs throughout the testing process. Interview data were analyzed using a modified grounded theory approach. In the absence of certainty about the implications of results, understanding of results is shaped by biomedical expert knowledge (BEK) and cultural expert knowledge (CEK). When there is a dearth of BEK, as in the case of receiving results of uncertain significance, participants rely on CEK, including religious/spiritual beliefs, "gut instinct," embodied knowledge, and social network informants. CEK is a powerful platform to guide understanding of prenatal genetic testing results. The utility of culturally situated expert knowledge during testing uncertainty emphasizes that decision-making occurs within discourses beyond the biomedical domain. These forms of "knowing" may be integrated into clinical consideration of efficacious patient assessment and counseling.

Test and Evaluation for Enhanced Security: A Quantitative Method to Incorporate Expert Knowledge into Test Planning Decisions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rizzo, Davinia; Blackburn, Mark

Complex systems are comprised of technical, social, political and environmental factors as well as the programmatic factors of cost, schedule and risk. Testing these systems for enhanced security requires expert knowledge in many different fields. It is important to test these systems to ensure effectiveness, but testing is limited to due cost, schedule, safety, feasibility and a myriad of other reasons. Without an effective decision framework for Test and Evaluation (T&E) planning that can take into consideration technical as well as programmatic factors and leverage expert knowledge, security in complex systems may not be assessed effectively. Therefore, this paper coversmore » the identification of the current T&E planning problem and an approach to include the full variety of factors and leverage expert knowledge in T&E planning through the use of Bayesian Networks (BN).« less

Analysis of underlying causes of inter-expert disagreement in retinopathy of prematurity diagnosis. Application of machine learning principles.

PubMed

Ataer-Cansizoglu, E; Kalpathy-Cramer, J; You, S; Keck, K; Erdogmus, D; Chiang, M F

2015-01-01

Inter-expert variability in image-based clinical diagnosis has been demonstrated in many diseases including retinopathy of prematurity (ROP), which is a disease affecting low birth weight infants and is a major cause of childhood blindness. In order to better understand the underlying causes of variability among experts, we propose a method to quantify the variability of expert decisions and analyze the relationship between expert diagnoses and features computed from the images. Identification of these features is relevant for development of computer-based decision support systems and educational systems in ROP, and these methods may be applicable to other diseases where inter-expert variability is observed. The experiments were carried out on a dataset of 34 retinal images, each with diagnoses provided independently by 22 experts. Analysis was performed using concepts of Mutual Information (MI) and Kernel Density Estimation. A large set of structural features (a total of 66) were extracted from retinal images. Feature selection was utilized to identify the most important features that correlated to actual clinical decisions by the 22 study experts. The best three features for each observer were selected by an exhaustive search on all possible feature subsets and considering joint MI as a relevance criterion. We also compared our results with the results of Cohen's Kappa [36] as an inter-rater reliability measure. The results demonstrate that a group of observers (17 among 22) decide consistently with each other. Mean and second central moment of arteriolar tortuosity is among the reasons of disagreement between this group and the rest of the observers, meaning that the group of experts consider amount of tortuosity as well as the variation of tortuosity in the image. Given a set of image-based features, the proposed analysis method can identify critical image-based features that lead to expert agreement and disagreement in diagnosis of ROP. Although tree-based features and various statistics such as central moment are not popular in the literature, our results suggest that they are important for diagnosis.

Integration of task level planning and diagnosis for an intelligent robot

NASA Technical Reports Server (NTRS)

Gerstenfeld, Arthur

1988-01-01

The use of robots in the future must go beyond present applications and will depend on the ability of a robot to adapt to a changing environment and to deal with unexpected scenarios (i.e., picking up parts that are not exactly where they were expected to be). The objective of this research is to demonstrate the feasibility of incorporating high level planning into a robot enabling it to deal with anomalous situations in order to minimize the need for constant human instruction. The heuristics can be used by a robot to apply information about previous actions towards accomplishing future objectives more efficiently. The system uses a decision network that represents the plan for accomplishing a task. This enables the robot to modify its plan based on results of previous actions. The system serves as a method for minimizing the need for constant human instruction in telerobotics. This paper describes the integration of expert systems and simulation as a valuable tool that goes far beyond this project. Simulation can be expected to be used increasingly as both hardware and software improve. Similarly, the ability to merge an expert system with simulation means that we can add intelligence to the system. A malfunctioning space satellite is described. The expert system uses a series of heuristics in order to guide the robot to the proper location. This is part of task level planning. The final part of the paper suggests directions for future research. Having shown the feasibility of an expert system embedded in a simulation, the paper then discusses how the system can be integrated with the MSFC graphics system.

Pricing and reimbursement frameworks in Central Eastern Europe: a decision tool to support choices.

PubMed

Kolasa, Katarzyna; Kalo, Zoltan; Hornby, Edward

2015-02-01

Given limited financial resources in the Central Eastern European (CEE) region, challenges in obtaining access to innovative medical technologies are formidable. The objective of this research was to develop a decision tree that supports decision makers and drug manufacturers from CEE region in their search for optimal innovative pricing and reimbursement scheme (IPRSs). A systematic literature review was performed to search for published IPRSs, and then ten experts from the CEE region were interviewed to ascertain their opinions on these schemes. In total, 33 articles representing 46 unique IPRSs were analyzed. Based on our literature review and subsequent expert input, key decision nodes and branches of the decision tree were developed. The results indicate that outcome-based schemes are better suited to deal with uncertainties surrounding cost effectiveness, while non-outcome-based schemes are more appropriate for pricing and budget impact challenges.

Knowledge producers or knowledge consumers? Argumentation and decision making about environmental management

NASA Astrophysics Data System (ADS)

JiméNez-Aleixandre, Maria-Pilar

2002-11-01

This paper describes a case study involving decision making and argumentation, in the context of wetland environmental management, by 11th-grade students (16-17 years old). The purpose was to study the components of knowledge and skills needed to reach a decision in socio-scientific contexts and to identify them in classroom discourse. The following dimensions of decision making were explored: the use of relevant knowledge to understand and make decisions about the problem; and the critical processing of sources of information and authority and the development of criteria for evaluating possible solutions to the problem. Students' conversations were recorded and analysed using Toulmin's (1958) and Walton's (1996) argument schemes. The students' arguments and warrants were compared with the argument of an external 'official' expert. Issues such as expert status, that is, who can be considered as a source of knowledge and authority and the participation of citizens in scientific practice are also discussed.

Treatment of acute burn blisters in unscheduled care settings.

PubMed

Payne, Sarah; Cole, Elaine

2012-09-01

Many patients with minor burns present at emergency departments and urgent care centres, where their management is often undertaken by experienced nurses rather than experts in treating burns. This article describes a small study of the clinical decision making that underpins nurses' management of minor burns in these non-specialist settings. The results suggest that, due to a lack of relevant research, nurses base their decisions on previous experience or expert colleagues' opinions and advice rather than on the evidence.

A center for commercial development of space: Real-time satellite mapping. Remote sensing-based agricultural information expert system

NASA Technical Reports Server (NTRS)

Hadipriono, Fabian C.; Diaz, Carlos F.; Merritt, Earl S.

1989-01-01

The research project results in a powerful yet user friendly CROPCAST expert system for use by a client to determine the crop yield production of a certain crop field. The study is based on the facts that heuristic assessment and decision making in agriculture are significant and dominate much of agribusiness. Transfer of the expert knowledge concerning remote sensing based crop yield production into a specific expert system is the key program in this study. A knowledge base consisting of a root frame, CROP-YIELD-FORECAST, and four subframes, namely, SATELLITE, PLANT-PHYSIOLOGY, GROUND, and MODEL were developed to accommodate the production rules obtained from the domain expert. The expert system shell Personal Consultant Plus version 4.0. was used for this purpose. An external geographic program was integrated to the system. This project is the first part of a completely built expert system. The study reveals that much effort was given to the development of the rules. Such effort is inevitable if workable, efficient, and accurate rules are desired. Furthermore, abundant help statements and graphics were included. Internal and external display routines add to the visual capability of the system. The work results in a useful tool for the client for making decisions on crop yield production.

Hesitant Fuzzy Thermodynamic Method for Emergency Decision Making Based on Prospect Theory.

PubMed

Ren, Peijia; Xu, Zeshui; Hao, Zhinan

2017-09-01

Due to the timeliness of emergency response and much unknown information in emergency situations, this paper proposes a method to deal with the emergency decision making, which can comprehensively reflect the emergency decision making process. By utilizing the hesitant fuzzy elements to represent the fuzziness of the objects and the hesitant thought of the experts, this paper introduces the negative exponential function into the prospect theory so as to portray the psychological behaviors of the experts, which transforms the hesitant fuzzy decision matrix into the hesitant fuzzy prospect decision matrix (HFPDM) according to the expectation-levels. Then, this paper applies the energy and the entropy in thermodynamics to take the quantity and the quality of the decision values into account, and defines the thermodynamic decision making parameters based on the HFPDM. Accordingly, a whole procedure for emergency decision making is conducted. What is more, some experiments are designed to demonstrate and improve the validation of the emergency decision making procedure. Last but not the least, this paper makes a case study about the emergency decision making in the firing and exploding at Port Group in Tianjin Binhai New Area, which manifests the effectiveness and practicability of the proposed method.

The Role of Evidence in the Decision-Making Process of Selecting Essential Medicines in Developing Countries: The Case of Tanzania

PubMed Central

Mori, Amani Thomas; Kaale, Eliangiringa Amos; Ngalesoni, Frida; Norheim, Ole Frithjof; Robberstad, Bjarne

2014-01-01

Background Insufficient access to essential medicines is a major health challenge in developing countries. Despite the importance of Standard Treatment Guidelines and National Essential Medicine Lists in facilitating access to medicines, little is known about how they are updated. This study aims to describe the process of updating the Standard Treatment Guidelines and National Essential Medicine List in Tanzania and further examines the criteria and the underlying evidence used in decision-making. Methods This is a qualitative study in which data were collected by in-depth interviews and document reviews. Interviews were conducted with 18 key informants who were involved in updating the Standard Treatment Guidelines and National Essential Medicine List. We used a thematic content approach to analyse the data. Findings The Standard Treatment Guidelines and National Essential Medicine List was updated by committees of experts who were recruited mostly from referral hospitals and the Ministry of Health and Social Welfare. Efficacy, safety, availability and affordability were the most frequently utilised criteria in decision-making, although these were largely based on experience rather than evidence. In addition, recommendations from international guidelines and medicine promotions also influenced decision-making. Cost-effectiveness, despite being an important criterion for formulary decisions, was not utilised. Conclusions Recent decisions about the selection of essential medicines in Tanzania were made by committees of experts who largely used experience and discretionary judgement, leaving evidence with only a limited role in decision-making process. There may be several reasons for the current limited use of evidence in decision-making, but one hypothesis that remains to be explored is whether training experts in evidence-based decision-making would lead to a better and more explicit use of evidence. PMID:24416293

Different profiles of decision making and physiology under varying levels of stress in trained military personnel.

PubMed

Gamble, Katherine R; Vettel, Jean M; Patton, Debra J; Eddy, Marianna D; Caroline Davis, F; Garcia, Javier O; Spangler, Derek P; Thayer, Julian F; Brooks, Justin R

2018-03-23

Decision making is one of the most vital processes we use every day, ranging from mundane decisions about what to eat to life-threatening choices such as how to avoid a car collision. Thus, the context in which our decisions are made is critical, and our physiology enables adaptive responses that account for how environmental stress influences our performance. The relationship between stress and decision making can additionally be affected by one's expertise in making decisions in high-threat environments, where experts can develop an adaptive response that mitigates the negative impacts of stress. In the present study, 26 male military personnel made friend/foe discriminations in an environment where we manipulated the level of stress. In the high-stress condition, participants received a shock when they incorrectly shot a friend or missed shooting a foe; in the low-stress condition, participants received a vibration for an incorrect decision. We characterized performance using signal detection theory to investigate whether a participant changed their decision criterion to avoid making an error. Results showed that under high-stress, participants made more false alarms, mistaking friends as foes, and this co-occurred with increased high frequency heart rate variability. Finally, we examined the relationship between decision making and physiology, and found that participants exhibited adaptive behavioral and physiological profiles under different stress levels. We interpret this adaptive profile as a marker of an expert's ingrained training that does not require top down control, suggesting a way that expert training in high-stress environments helps to buffer negative impacts of stress on performance. Published by Elsevier B.V.

The role of evidence in the decision-making process of selecting essential medicines in developing countries: the case of Tanzania.

PubMed

Mori, Amani Thomas; Kaale, Eliangiringa Amos; Ngalesoni, Frida; Norheim, Ole Frithjof; Robberstad, Bjarne

2014-01-01

Insufficient access to essential medicines is a major health challenge in developing countries. Despite the importance of Standard Treatment Guidelines and National Essential Medicine Lists in facilitating access to medicines, little is known about how they are updated. This study aims to describe the process of updating the Standard Treatment Guidelines and National Essential Medicine List in Tanzania and further examines the criteria and the underlying evidence used in decision-making. This is a qualitative study in which data were collected by in-depth interviews and document reviews. Interviews were conducted with 18 key informants who were involved in updating the Standard Treatment Guidelines and National Essential Medicine List. We used a thematic content approach to analyse the data. The Standard Treatment Guidelines and National Essential Medicine List was updated by committees of experts who were recruited mostly from referral hospitals and the Ministry of Health and Social Welfare. Efficacy, safety, availability and affordability were the most frequently utilised criteria in decision-making, although these were largely based on experience rather than evidence. In addition, recommendations from international guidelines and medicine promotions also influenced decision-making. Cost-effectiveness, despite being an important criterion for formulary decisions, was not utilised. Recent decisions about the selection of essential medicines in Tanzania were made by committees of experts who largely used experience and discretionary judgement, leaving evidence with only a limited role in decision-making process. There may be several reasons for the current limited use of evidence in decision-making, but one hypothesis that remains to be explored is whether training experts in evidence-based decision-making would lead to a better and more explicit use of evidence.

TOPSIS-based consensus model for group decision-making with incomplete interval fuzzy preference relations.

PubMed

Liu, Fang; Zhang, Wei-Guo

2014-08-01

Due to the vagueness of real-world environments and the subjective nature of human judgments, it is natural for experts to estimate their judgements by using incomplete interval fuzzy preference relations. In this paper, based on the technique for order preference by similarity to ideal solution method, we present a consensus model for group decision-making (GDM) with incomplete interval fuzzy preference relations. To do this, we first define a new consistency measure for incomplete interval fuzzy preference relations. Second, a goal programming model is proposed to estimate the missing interval preference values and it is guided by the consistency property. Third, an ideal interval fuzzy preference relation is constructed by using the induced ordered weighted averaging operator, where the associated weights of characterizing the operator are based on the defined consistency measure. Fourth, a similarity degree between complete interval fuzzy preference relations and the ideal one is defined. The similarity degree is related to the associated weights, and used to aggregate the experts' preference relations in such a way that more importance is given to ones with the higher similarity degree. Finally, a new algorithm is given to solve the GDM problem with incomplete interval fuzzy preference relations, which is further applied to partnership selection in formation of virtual enterprises.

Fuzzy logic system able to detect interesting areas of a video sequence

NASA Astrophysics Data System (ADS)

De Vleeschouwer, Christophe; Marichal, Xavier; Delmot, Thierry; Macq, Benoit M. M.

1997-06-01

This paper introduces an automatic tool able to analyze the picture according to the semantic interest an observer attributes to its content. Its aim is to give a 'level of interest' to the distinct areas of the picture extracted by any segmentation tool. For the purpose of dealing with semantic interpretation of images, a single criterion is clearly insufficient because the human brain, due to its a priori knowledge and its huge memory of real-world concrete scenes, combines different subjective criteria in order to assess its final decision. The developed method permits such combination through a model using assumptions to express some general subjective criteria. Fuzzy logic enables the user to encode knowledge in a form that is very close the way experts think about the decision process. This fuzzy modeling is also well suited to represent multiple collaborating or even conflicting experts opinions. Actually, the assumptions are verified through a non-hierarchical strategy that considers them in a random order, each partial result contributing to the final one. Presented results prove that the tool is effective for a wide range of natural pictures. It is versatile and flexible in that it can be used stand-alone or can take into account any a priori knowledge about the scene.

Expert Intraoperative Judgment and Decision-Making: Defining the Cognitive Competencies for Safe Laparoscopic Cholecystectomy.

PubMed

Madani, Amin; Watanabe, Yusuke; Feldman, Liane S; Vassiliou, Melina C; Barkun, Jeffrey S; Fried, Gerald M; Aggarwal, Rajesh

2015-11-01

Bile duct injuries from laparoscopic cholecystectomy remain a significant source of morbidity and are often the result of intraoperative errors in perception, judgment, and decision-making. This qualitative study aimed to define and characterize higher-order cognitive competencies required to safely perform a laparoscopic cholecystectomy. Hierarchical and cognitive task analyses for establishing a critical view of safety during laparoscopic cholecystectomy were performed using qualitative methods to map the thoughts and practices that characterize expert performance. Experts with more than 5 years of experience, and who have performed at least 100 laparoscopic cholecystectomies, participated in semi-structured interviews and field observations. Verbal data were transcribed verbatim, supplemented with content from published literature, coded, thematically analyzed using grounded-theory by 2 independent reviewers, and synthesized into a list of items. A conceptual framework was created based on 10 interviews with experts, 9 procedures, and 18 literary sources. Experts included 6 minimally invasive surgeons, 2 hepato-pancreatico-biliary surgeons, and 2 acute care general surgeons (median years in practice, 11 [range 8 to 14]). One hundred eight cognitive elements (35 [32%] related to situation awareness, 47 [44%] involving decision-making, and 26 [24%] action-oriented subtasks) and 75 potential errors were identified and categorized into 6 general themes and 14 procedural tasks. Of the 75 potential errors, root causes were mapped to errors in situation awareness (24 [32%]), decision-making (49 [65%]), or either one (61 [81%]). This study defines the competencies that are essential to establishing a critical view of safety and avoiding bile duct injuries during laparoscopic cholecystectomy. This framework may serve as the basis for instructional design, assessment tools, and quality-control metrics to prevent injuries and promote a culture of patient safety. Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

E-mail as the Appropriate Method of Communication for the Decision-Maker When Soliciting Advice for an Intellective Decision Task.

PubMed

Prahl, Andrew; Dexter, Franklin; Swol, Lyn Van; Braun, Michael T; Epstein, Richard H

2015-09-01

For many problems in operating room and anesthesia group management, there are tasks with optimal decisions, and yet experienced personnel tend to make decisions that are worse or no better than random chance. Such decisions include staff scheduling, case scheduling, moving cases among operating rooms, and choosing patient arrival times. In such settings, operating room management leadership decision-making should typically be autocratic rather than participative. Autocratic-style decision-making calls for managers to solicit and consider feedback from stakeholders in the decision outcome but to make the decision themselves using their expert knowledge and the facts received. For this to be effective, often the manager will obtain expert advice from outside the organization (e.g., health system). In this narrative review, we evaluate the advantages and disadvantages of using prompt asynchronous written communication (i.e., e-mail) as a communication channel for such interaction between a decision-maker (manager) and advisor. A detailed Appendix (Supplemental Digital Content, http://links.lww.com/AA/B72) lists each observational and experimental result. We find that the current ubiquitous role of e-mail for such communication is appropriate. Its benefits include improved time management via asynchronicity, low cognitive load (e.g., relative to Web conferencing), the ability to hide undesirable and irrelevant cues (e.g., physical appearance), the appropriateness of adding desirable cues (e.g., titles and degrees), the opportunity to provide written expression of confidence, and the ability for the advisor to demonstrate the answer for the decision-maker. Given that the manager is e-mailing an advisor whose competence the manager trusts, it is unnecessary to use a richer communication channel to develop trust. Finally, many of the limitations of e-mail can be rectified through training. We expect that decades from now, e-mail (i.e., asynchronous writing) between an expert and decision-maker will remain the dominant means of communication for intellective tasks.

A Strategic Plan for Support of Expert Systems in Organizations.

DTIC Science & Technology

1987-09-01

sequencing Job orders 1 2Li no. of companies answering this question: 34 m--t common use of expert systems: diagnosis 98 p pl 7 N71Z RPN 49r " ETF 1W...69 (December 1986). 16. Gold , Jordan. "Do-It-Yourself Expert Systems," Comouter Decisions: 76-81 (January 14, 1986). 17. Guterl, Fred U. "Computers

Sustainment of Individual and Collective Future Combat Skills: Modeling and Research Methods

DTIC Science & Technology

2010-01-01

expertise: Novice, Advanced Beginner , Competent, Proficient, and Expert. According to this conceptualization, tactical leaders develop cognitively...to equipment or containers. • Checklists, flowcharts , worksheets, decision tables, and system-fault tables. • Written instructions (e.g., on...novice; (2) advanced beginner ; (3) competent; (4) proficient; and (5) expert. Going from novice to expert, each level of skill development reflects

The Designer-by-Assignment in Practice: Instructional Design Thinking of Subject Matter Experts

ERIC Educational Resources Information Center

Pesce, Sandra V.

2012-01-01

Designers-by-assignment, or subject matter experts (SMEs) who are pressed into training service, have become common in the workplace. A review of more than 24 studies on expert and novice instructional designers, however, revealed that little is known about how designers-by-assignment think about design and make design decisions in the field. A…

What must be the Pillars of Iran’s Health System in 2025? Values and Principles of Health System Reform Plan

PubMed Central

RAJABI, Fateme; ESMAILZADEH, Hamid; ROSTAMIGOORAN, Narges; MAJDZADEH, Reza

2013-01-01

Background: Preparing long term reformatory plan for the health system, like other macro plans, requires guiding principles which is according to the values, and as a bridge, connect the ideals and values to the goals. This study was designed with the purpose of explaining the values and principles of health system, and as a pre-requisite to compilation of Iran’s health system reform plan at 2025. Method: The document of values and principles of health system reform plan for 2025 was developed by reviewing the literature and receiving the opinions of senior experts of health system, and was criticized in focus group discussion sessions of experts and decision makers. Results: The values of Iran are: dignity of human, the right to maximum attainable level of health, comprehensive health, equity and social cohesion. The principles of this health system include: institutionalizing the ethical values, responsiveness and accountability, equitable access (utilization), prevention and health promotion, community participation, inter-sectoral collaboration, integrated stewardship, benefit from innovation and desired technology, human resources promotion and excellence and harmony. Conclusion: Based on the perception of cultural and religious teachings in Iran, protecting of human dignity and human prosperity are the ultimate social goal. In this sense, health and healthy humans, in its holistic concept (physical, mental, social health and spiritual) are the center and development in any form should lead to the human prosperity in a way that each of the individuals could enjoy the maximum attainable level of health in its holistic meaning and in a faire manner. PMID:23515322

Expert Systems: Tutors, Tools, and Tutees.

ERIC Educational Resources Information Center

Lippert, Renate C.

1989-01-01

Discusses the current status, research, and practical implications of artificial intelligence and expert systems in education. Topics discussed include computer-assisted instruction; intelligent computer-assisted instruction; intelligent tutoring systems; instructional strategies involving the creation of knowledge bases; decision aids;…

A Novel Framework for Characterizing Exposure-Related ...

EPA Pesticide Factsheets

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing our ABM upon a needs-based artificial intelligence (AI) system, we create agents that mimic human decisions on these exposure-relevant behaviors. In a case study of adults, we use the AI to predict the inter-individual variation in the start time and duration of four behaviors: sleeping, eating, commuting, and working. The results demonstrate that the ABM can capture both inter-individual variation and how decisions on one behavior can affect subsequent behaviors. Preset NERL's research on the use of agent based modeling in exposure assessments. To obtain feed back on the approach from the leading experts in the field.

Data dialogues: critical connections for designing and implementing future nanomaterial research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powers, Christina M.; Grieger, Khara D.; Beaudrie, Christian

2014-11-07

Individuals and organizations in the engineered nanomaterial (ENM) community have increasingly recognized two related but distinct concerns: 1) discordant data due to differences in experimental design (e.g., material characteristics, experimental model, exposure concentration) or reporting (e.g., dose metric, material characterization details), and 2) a lack of data to inform decisions about ENM environmental, health, and safety (EHS). As one way to help address these issues, this Commentary discusses the important role of “data dialogues” or structured discussions between ENM researchers in EHS fields (e.g., toxicology, exposure science, and industrial hygiene) and decision makers who use the data researchers collect. Themore » importance of these structured discussions is examined here in the context of barriers, solutions, and incentives: barriers to developing research relevant for human and ecological risk assessments; potential solutions to overcome such barriers; and incentives to help implement these or other solutions. These barriers, solutions, and incentives were identified by a group of expert stakeholders and ENM community members at the December 2013 Society for Risk Analysis panel discussion on research needed to support decision making for multiwalled carbon nanotubes (MWCNTs). Key topics discussed by experts and ENM community members include: (1) the value of researchers collaborating with EHS decision makers (e.g., risk analysts, product developers, regulators) to design research that can inform ENM EHS-related decisions (e.g., occupational exposure limits, product safety determinations), (2) the importance of funding incentives for such collaborative research, (3) the need to improve mechanisms for data-sharing within and between sectors (e.g., academia, government, and industry), and (4) the critical need to educate the “next generation” of nanotechnology researchers in EHS topics (e.g., risk assessment, risk management). In presenting these outcomes, this Commentary is not intended to conclude the conversation that took place in December 2013 but rather to support a broader dialogue that helps ensure important risk assessment questions are answered for ENMs.« less

PVEX: An expert system for producibility/value engineering

NASA Technical Reports Server (NTRS)

Lam, Chun S.; Moseley, Warren

1991-01-01

PVEX is described as an expert system that solves the problem of selection of the material and process in missile manufacturing. The producibility and the value problem has been deeply studied in the past years, and was written in dBase III and PROLOG before. A new approach is presented in that the solution is achieved by introducing hypothetical reasoning, heuristic criteria integrated with a simple hypertext system and shell programming. PVEX combines KMS with Unix scripts which graphically depicts decision trees. The decision trees convey high level qualitative problem solving knowledge to users, and a stand-alone help facility and technical documentation is available through KMS. The system developed is considerably less development costly than any other comparable expert system.

Validation of Pre-operative Patient Self-Assessment of Cardiac Risk for Non-Cardiac Surgery: Foundations for Decision Support

PubMed Central

Manaktala, Sharad; Rockwood, Todd; Adam, Terrence J.

2013-01-01

Objectives: To better characterize patient understanding of their risk of cardiac complications from non-cardiac surgery and to develop a patient driven clinical decision support system for preoperative patient risk management. Methods: A patient-driven preoperative self-assessment decision support tool for perioperative assessment was created. Patient’ self-perception of cardiac risk and self-report data for risk factors were compared with gold standard preoperative physician assessment to evaluate agreement. Results: The patient generated cardiac risk profile was used for risk score generation and had excellent agreement with the expert physician assessment. However, patient subjective self-perception risk of cardiovascular complications had poor agreement with expert assessment. Conclusion: A patient driven cardiac risk assessment tool provides a high degree of agreement with expert provider assessment demonstrating clinical feasibility. The limited agreement between provider risk assessment and patient self-perception underscores a need for further work including focused preoperative patient education on cardiac risk. PMID:24551384

Contextual information renders experts vulnerable to making erroneous identifications.

PubMed

Dror, Itiel E; Charlton, David; Péron, Ailsa E

2006-01-06

We investigated whether experts can objectively focus on feature information in fingerprints without being misled by extraneous information, such as context. We took fingerprints that have previously been examined and assessed by latent print experts to make positive identification of suspects. Then we presented these same fingerprints again, to the same experts, but gave a context that suggested that they were a no-match, and hence the suspects could not be identified. Within this new context, most of the fingerprint experts made different judgements, thus contradicting their own previous identification decisions. Cognitive aspects involved in biometric identification can explain why experts are vulnerable to make erroneous identifications.

[Medical expert assessment in criminal processes from the legal viewpoint].

PubMed

Ulsenheimer, K

1996-11-01

In the area of medical professional blunder, the medical expert witness is the one participant in a trial whose statement is practically decisive for the court or the prosecutor. Legally, the responsibility remains naturally in the legal hand as the expert witness is only the assistant of the judge. The most important demands on the expert witness are strict objectiveness including towards the colleague, no independent inquiries or interrogations, comprehensive processing of the expert assessment, readiness to revise a written expert assessment according to better knowledge or new facts, independence from the client, no legal comments, clarity of language and intellectual honesty.

Barcelona 2002: law, ethics, and human rights. HIV testing for peacekeeping forces: legal and human rights issues.

PubMed

Jürgens, Ralf

2002-12-01

In 2001, the United Nations Security Council established an Expert Panel to study the issue of whether the UN should institute HIV testing of peacekeeping personnel. This article, based on a 9 July 2002 presentation to the XIV International AIDS Conference (abstract TuOrG1173), reports on the findings of a paper prepared for the Expert Panel by the Canadian HIV/AIDS Legal Network. The paper examined whether it is permissible for the UN to implement mandatory HIV testing of its peacekeeping personnel, and whether HIV-positive UN peacekeeping personnel should be excluded or restricted from service on the basis of their HIV status or HIV disease progression. The article describes some of the court cases in which these issues have been considered; discusses the importance of analyzing such issues in the context of a human rights-based approach to the pandemic; and formulates a series of key principles for guiding UN decision-making. The article concludes that a policy of mandatory HIV testing for all UN peacekeeping personnel cannot be justified on the basis that it is required in order to assess their physical and mental capacity for service; that HIV-positive peacekeeping personnel cannot be excluded from service based on their HIV status alone, but only on their ability to perform their duties; and that the UN cannot resort to mandatory HIV testing for all UN peacekeeping personnel to protect the health and safety of HIV-negative personnel unless it can demonstrate that alternatives to such a policy would not reduce the risk sufficiently. In the end, the Expert Panel unanimously rejected mandatory testing and instead endorsed voluntary HIV counselling and testing for UN peacekeeping personnel.

An evaluation of an expert system for detecting critical events during anesthesia in a human patient simulator: a prospective randomized controlled study.

PubMed

Görges, Matthias; Winton, Pamela; Koval, Valentyna; Lim, Joanne; Stinson, Jonathan; Choi, Peter T; Schwarz, Stephan K W; Dumont, Guy A; Ansermino, J Mark

2013-08-01

Perioperative monitoring systems produce a large amount of uninterpreted data, use threshold alarms prone to artifacts, and rely on the clinician to continuously visually track changes in physiological data. To address these deficiencies, we developed an expert system that provides real-time clinical decisions for the identification of critical events. We evaluated the efficacy of the expert system for enhancing critical event detection in a simulated environment. We hypothesized that anesthesiologists would identify critical ventilatory events more rapidly and accurately with the expert system. We used a high-fidelity human patient simulator to simulate an operating room environment. Participants managed 4 scenarios (anesthetic vapor overdose, tension pneumothorax, anaphylaxis, and endotracheal tube cuff leak) in random order. In 2 of their 4 scenarios, participants were randomly assigned to the expert system, which provided trend-based alerts and potential differential diagnoses. Time to detection and time to treatment were measured. Workload questionnaires and structured debriefings were completed after each scenario, and a usability questionnaire at the conclusion of the session. Data were analyzed using a mixed-effects linear regression model; Fisher exact test was used for workload scores. Twenty anesthesiology trainees and 15 staff anesthesiologists with a combined median (range) of 36 (29-66) years of age and 6 (1-38) years of anesthesia experience participated. For the endotracheal tube cuff leak, the expert system caused mean reductions of 128 (99% confidence interval [CI], 54-202) seconds in time to detection and 140 (99% CI, 79-200) seconds in time to treatment. In the other 3 scenarios, a best-case decrease of 97 seconds (lower 99% CI) in time to diagnosis for anaphylaxis and a worst-case increase of 63 seconds (upper 99% CI) in time to treatment for anesthetic vapor overdose were found. Participants were highly satisfied with the expert system (median score, 2 on a scale of 1-7). Based on participant debriefings, we identified avoidance of task fixation, reassurance to initiate invasive treatment, and confirmation of a suspected diagnosis as 3 safety-critical areas. When using the expert system, clinically important and statistically significant decreases in time to detection and time to treatment were observed for the endotracheal tube cuff Leak scenario. The observed differences in the other 3 scenarios were much smaller and not statistically significant. Further evaluation is required to confirm the clinical utility of real-time expert systems for anesthesia.

Integrated studies on the use of cognitive task analysis to capture surgical expertise for central venous catheter placement and open cricothyrotomy.

PubMed

Yates, Kenneth; Sullivan, Maura; Clark, Richard

2012-01-01

Cognitive task analysis (CTA) methods were used for 2 surgical procedures to determine (1) the extent that experts omitted critical information, (2) the number of experts required to capture the optimalamount of information, and (3) the effectiveness of a CTA-informed curriculum. Six expert physicians for both the central venous catheter placement and open cricothyrotomy were interviewed. The transcripts were coded, corrected, and aggregated as a "gold standard." The information captured for each surgeon was then analyzed against the gold standard. Experts omitted an average of 34% of the decisions for the central venous catheter and 77% of the decisions for the Cric. Three to 4 experts were required to capture the optimal amount of information. A significant positive effect on performance (t([21]) = 2.08, P = .050), and self-efficacy ratings (t([18]) = 2.38, P = .029) were found for the CTA-informed curriculum for cricothyrotomy. CTA is an effective method to capture expertise in surgery and a valuable component to improve surgical training. Copyright © 2012 Elsevier Inc. All rights reserved.

Developing Effective Communications about Extreme Weather Risks.

NASA Astrophysics Data System (ADS)

Bruine de Bruin, W.

2014-12-01

Members of the general public often face complex decisions about the risks that they face, including those associated with extreme weather and climate change adaptation. Scientific experts may be asked to develop communications with the goal of improving people's understanding of weather and climate risks, and informing people's decisions about how to protect against these risks. Unfortunately, scientific experts' communication efforts may fail if they lack information about what people need or want to know to make more informed decisions or what wording people prefer use to describe relevant concepts. This presentation provides general principles for developing effective risk communication materials that aim for widespread dissemination, such as brochures and websites. After a brief review of the social science evidence on how to design effective risk communication materials, examples will focus on communications about extreme weather events and climate change. Specifically, data will be presented from ongoing projects on flood risk perception, public preparedness for heat waves, and public perceptions of climate change. The presentation will end with specific recommendations about how to improve recipients' understanding about risks and inform decisions. These recommendations should be useful to scientific experts who aim to communicate about extreme weather, climate change, or other risks.

The CBT Advisor: An Expert System Program for Making Decisions about CBT.

ERIC Educational Resources Information Center

Kearsley, Greg

1985-01-01

Discusses structure, credibility, and use of the Computer Based Training (CBT) Advisor, an expert system designed to help managers make judgements about course selection, system selection, cost/benefits, development effort, and probable success of CBT projects. (MBR)

Use of artificial intelligence in supervisory control

NASA Technical Reports Server (NTRS)

Cohen, Aaron; Erickson, Jon D.

1989-01-01

Viewgraphs describing the design and testing of an intelligent decision support system called OFMspert are presented. In this expert system, knowledge about the human operator is represented through an operator/system model referred to as the OFM (Operator Function Model). OFMspert uses the blackboard model of problem solving to maintain a dynamic representation of operator goals, plans, tasks, and actions given previous operator actions and current system state. Results of an experiment to assess OFMspert's intent inferencing capability are outlined. Finally, the overall design philosophy for an intelligent tutoring system (OFMTutor) for operators of complex dynamic systems is summarized.

20 CFR 405.220 - Decision by the Federal reviewing official.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Decision by the Federal reviewing official. 405.220 Section 405.220 Employees' Benefits SOCIAL SECURITY ADMINISTRATION ADMINISTRATIVE REVIEW... Medical and Vocational Expert System before making a decision. At all times, the Federal reviewing...

77 FR 6092 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-07

... systems which provide a way to compare surveillance and detection equipment and make informed purchasing decisions. Due to rapid changes and inventions in technology, the market survey must be updated to ensure... will be analyzed by a team of subject matter experts in detection and decision analysis. Decision...

Shared Problem Models and Crew Decision Making

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Statler, Irving C. (Technical Monitor)

1994-01-01

The importance of crew decision making to aviation safety has been well established through NTSB accident analyses: Crew judgment and decision making have been cited as causes or contributing factors in over half of all accidents in commercial air transport, general aviation, and military aviation. Yet the bulk of research on decision making has not proven helpful in improving the quality of decisions in the cockpit. One reason is that traditional analytic decision models are inappropriate to the dynamic complex nature of cockpit decision making and do not accurately describe what expert human decision makers do when they make decisions. A new model of dynamic naturalistic decision making is offered that may prove more useful for training or aiding cockpit decision making. Based on analyses of crew performance in full-mission simulation and National Transportation Safety Board accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation and reflect the crew's metacognitive skill. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relation between communication that serves to build performance. Implications of these findings for crew training will be discussed.

Semi-quantitative assessment of disease risks at the human, livestock, wildlife interface for the Republic of Korea using a nationwide survey of experts: A model for other countries.

PubMed

Hwang, J; Lee, K; Walsh, D; Kim, S W; Sleeman, J M; Lee, H

2018-02-01

Wildlife-associated diseases and pathogens have increased in importance; however, management of a large number of diseases and diversity of hosts is prohibitively expensive. Thus, the determination of priority wildlife pathogens and risk factors for disease emergence is warranted. We used an online questionnaire survey to assess release and exposure risks, and consequences of wildlife-associated diseases and pathogens in the Republic of Korea (ROK). We also surveyed opinions on pathways for disease exposure, and risk factors for disease emergence and spread. For the assessment of risk, we employed a two-tiered, statistical K-means clustering algorithm to group diseases into three levels (high, medium and low) of perceived risk based on release and exposure risks, societal consequences and the level of uncertainty of the experts' opinions. To examine the experts' perceived risk of routes of introduction of pathogens and disease amplification and spread, we used a Bayesian, multivariate normal order-statistics model. Six diseases or pathogens, including four livestock and two wildlife diseases, were identified as having high risk with low uncertainty. Similarly, 13 diseases were characterized as having high risk with medium uncertainty with three of these attributed to livestock, six associated with human disease, and the remainder having the potential to affect human, livestock and wildlife (i.e., One Health). Lastly, four diseases were described as high risk with high certainty, and were associated solely with fish diseases. Experts identified migration of wildlife, international human movement and illegal importation of wildlife as the three routes posing the greatest risk of pathogen introduction into ROK. Proximity of humans, livestock and wildlife was the most significant risk factor for promoting the spread of wildlife-associated diseases and pathogens, followed by high density of livestock populations, habitat loss and environmental degradation, and climate change. This study provides useful information to decision makers responsible for allocating resources to address disease risks. This approach provided a rapid, cost-effective method of risk assessment of wildlife-associated diseases and pathogens for which the published literature is sparse. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Improving Safe and Effective Use of Drugs in Pregnancy and Lactation: Workshop Summary.

PubMed

Riley, Laura E; Cahill, Alison G; Beigi, Richard; Savich, Renate; Saade, George

2017-07-01

In February 2015, given high rates of use of medications by pregnant women and the relative lack of data on safety and efficacy of many drugs utilized in pregnancy, the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the Society for Maternal-Fetal Medicine (SMFM), the American College of Obstetricians and Gynecologists (ACOG), and the American Academy of Pediatrics (AAP) convened a group of experts to review the "current" state of the clinical care and science regarding medication use during the perinatal period. The expert panel chose select medications to demonstrate what existing safety and efficacy data may be available for clinicians and patients when making decisions about use in pregnancy or lactation. Furthermore, these example medications also provided opportunities to highlight where data are lacking, thus forming a list of research gaps. Last, after reviewing the existing vaccine safety surveillance system as well as the legislative history surrounding the use of drugs for pediatric diseases, the expert panel made specific recommendations concerning policy efforts to stimulate more research and regulatory attention on drugs for pregnant and lactating women. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh

2015-01-15

Highlights: • We review Municipal Solid Waste Management studies with focus on multiple stakeholders. • We focus on studies with multi-criteria decision analysis methods and discover their trends. • Most studies do not offer solutions for situations where stakeholders compete for more benefits or have unequal voting powers. • Governments and experts are the most participated stakeholders and AHP is the most dominant method. - Abstract: Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, andmore » finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies.« less

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

A Person-Centered Approach to Financial Capacity Assessment: Preliminary Development of a New Rating Scale

PubMed Central

Lichtenberg, Peter A.; Stoltman, Jonathan; Ficker, Lisa J.; Iris, Madelyn; Mast, Benjamin

2014-01-01

Financial exploitation and financial capacity issues often overlap when a gerontologist assesses whether an older adult’s financial decision is an autonomous, capable choice. Our goal is to describe a new conceptual model for assessing financial decisions using principles of person-centered approaches and to introduce a new instrument, the Lichtenberg Financial Decision Rating Scale (LFDRS). We created a conceptual model, convened meetings of experts from various disciplines to critique the model and provide input on content and structure, and select final items. We then videotaped administration of the LFDRS to five older adults and had 10 experts provide independent ratings. The LFDRS demonstrated good to excellent inter-rater agreement. The LFDRS is a new tool that allows gerontologists to systematically gather information about a specific financial decision and the decisional abilities in question. PMID:25866438

A Person-Centered Approach to Financial Capacity Assessment: Preliminary Development of a New Rating Scale.

PubMed

Lichtenberg, Peter A; Stoltman, Jonathan; Ficker, Lisa J; Iris, Madelyn; Mast, Benjamin

2015-01-01

Financial exploitation and financial capacity issues often overlap when a gerontologist assesses whether an older adult's financial decision is an autonomous, capable choice. Our goal is to describe a new conceptual model for assessing financial decisions using principles of person-centered approaches and to introduce a new instrument, the Lichtenberg Financial Decision Rating Scale (LFDRS). We created a conceptual model, convened meetings of experts from various disciplines to critique the model and provide input on content and structure, and select final items. We then videotaped administration of the LFDRS to five older adults and had 10 experts provide independent ratings. The LFDRS demonstrated good to excellent inter-rater agreement. The LFDRS is a new tool that allows gerontologists to systematically gather information about a specific financial decision and the decisional abilities in question.

Exposure Models for the Prior Distribution in Bayesian Decision Analysis for Occupational Hygiene Decision Making

PubMed Central

Lee, Eun Gyung; Kim, Seung Won; Feigley, Charles E.; Harper, Martin

2015-01-01

This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure. PMID:23252451

SeTES, a Self-Teaching Expert System for the analysis, design and prediction of gas production from shales and a prototype for a new generation of Expert Systems in the Earth Sciences

NASA Astrophysics Data System (ADS)

Kuzma, H. A.; Boyle, K.; Pullman, S.; Reagan, M. T.; Moridis, G. J.; Blasingame, T. A.; Rector, J. W.; Nikolaou, M.

2010-12-01

A Self Teaching Expert System (SeTES) is being developed for the analysis, design and prediction of gas production from shales. An Expert System is a computer program designed to answer questions or clarify uncertainties that its designers did not necessarily envision which would otherwise have to be addressed by consultation with one or more human experts. Modern developments in computer learning, data mining, database management, web integration and cheap computing power are bringing the promise of expert systems to fruition. SeTES is a partial successor to Prospector, a system to aid in the identification and evaluation of mineral deposits developed by Stanford University and the USGS in the late 1970s, and one of the most famous early expert systems. Instead of the text dialogue used in early systems, the web user interface of SeTES helps a non-expert user to articulate, clarify and reason about a problem by navigating through a series of interactive wizards. The wizards identify potential solutions to queries by retrieving and combining together relevant records from a database. Inferences, decisions and predictions are made from incomplete and noisy inputs using a series of probabilistic models (Bayesian Networks) which incorporate records from the database, physical laws and empirical knowledge in the form of prior probability distributions. The database is mainly populated with empirical measurements, however an automatic algorithm supplements sparse data with synthetic data obtained through physical modeling. This constitutes the mechanism for how SeTES self-teaches. SeTES’ predictive power is expected to grow as users contribute more data into the system. Samples are appropriately weighted to favor high quality empirical data over low quality or synthetic data. Finally, a set of data visualization tools digests the output measurements into graphical outputs.

Expert Decision-Making in Naturalistic Environments: A Summary of Research

DTIC Science & Technology

2005-03-01

a number of descriptive decision theories arose (Plous, 1993). One of these is the rational choice model of decision - making (Janis & Mann, 1977...possible association between time pressure and increased levels of emotion . To date, the role played by emotion in decision - making has not been given... rational choice model seems to describe some decision events and Janis and Mann (1977) have highlighted emotion as a potential influence on decision

Second-line treatment for metastatic clear cell renal cell cancer: experts' consensus algorithms.

PubMed

Rothermundt, C; von Rappard, J; Eisen, T; Escudier, B; Grünwald, V; Larkin, J; McDermott, D; Oldenburg, J; Porta, C; Rini, B; Schmidinger, M; Sternberg, C N; Putora, P M

2017-04-01

Second-line systemic treatment options for metastatic clear cell renal cell cancer (mccRCC) are diverse and treatment strategies are variable among experts. Our aim was to investigate the approach for the second-line treatment after first-line therapy with a tyrosine kinase inhibitor (TKI). Recently two phase III trials have demonstrated a potential role for nivolumab (NIV) and cabozantinib (CAB) in this setting. We aimed to estimate the impact of these trials on clinical decision making. Eleven international experts were asked to provide their treatment strategies for second-line systemic therapy for mccRCC in the current setting and once NIV and CAB will be approved and available. The treatment strategies were analyzed with the objective consensus approach. The analysis of the decision trees revealed everolimus (EVE), axitinib (AXI), NIV and TKI switch (sTKI) as therapeutic options after first-line TKI therapy in the current situation and mostly NIV and CAB in the future setting. The most commonly used criteria for treatment decisions were duration of response, TKI tolerance and zugzwang a composite of several related criteria. In contrast to the first-line setting, recommendations for second-line systemic treatment of mccRCC among experts were not as heterogeneous. The agents mostly used after disease progression on a first-line TKI included: EVE, AXI, NIV and sTKI. In the future setting of NIV and CAB availability, NIV was the most commonly chosen drug, whereas several experts identified situations where CAB would be preferred.

Technical Assistance for States | State, Local, and Tribal Governments |

Science.gov Websites

on energy efficiency and renewable energy policies and issues for state and local government decision issues for state and local government decision makers. The expert assistance is intended to support legislators, regulators, state agencies, and their staff members in making informed decisions about solar

Accuracy of computer-aided diagnosis based on narrow-band imaging endocytoscopy for diagnosing colorectal lesions: comparison with experts.

PubMed

Misawa, Masashi; Kudo, Shin-Ei; Mori, Yuichi; Takeda, Kenichi; Maeda, Yasuharu; Kataoka, Shinichi; Nakamura, Hiroki; Kudo, Toyoki; Wakamura, Kunihiko; Hayashi, Takemasa; Katagiri, Atsushi; Baba, Toshiyuki; Ishida, Fumio; Inoue, Haruhiro; Nimura, Yukitaka; Oda, Msahiro; Mori, Kensaku

2017-05-01

Real-time characterization of colorectal lesions during colonoscopy is important for reducing medical costs, given that the need for a pathological diagnosis can be omitted if the accuracy of the diagnostic modality is sufficiently high. However, it is sometimes difficult for community-based gastroenterologists to achieve the required level of diagnostic accuracy. In this regard, we developed a computer-aided diagnosis (CAD) system based on endocytoscopy (EC) to evaluate cellular, glandular, and vessel structure atypia in vivo. The purpose of this study was to compare the diagnostic ability and efficacy of this CAD system with the performances of human expert and trainee endoscopists. We developed a CAD system based on EC with narrow-band imaging that allowed microvascular evaluation without dye (ECV-CAD). The CAD algorithm was programmed based on texture analysis and provided a two-class diagnosis of neoplastic or non-neoplastic, with probabilities. We validated the diagnostic ability of the ECV-CAD system using 173 randomly selected EC images (49 non-neoplasms, 124 neoplasms). The images were evaluated by the CAD and by four expert endoscopists and three trainees. The diagnostic accuracies for distinguishing between neoplasms and non-neoplasms were calculated. ECV-CAD had higher overall diagnostic accuracy than trainees (87.8 vs 63.4%; [Formula: see text]), but similar to experts (87.8 vs 84.2%; [Formula: see text]). With regard to high-confidence cases, the overall accuracy of ECV-CAD was also higher than trainees (93.5 vs 71.7%; [Formula: see text]) and comparable to experts (93.5 vs 90.8%; [Formula: see text]). ECV-CAD showed better diagnostic accuracy than trainee endoscopists and was comparable to that of experts. ECV-CAD could thus be a powerful decision-making tool for less-experienced endoscopists.

Uncovering Professional Attitudes Toward Treatment of Rare Carcinomas of the Breast: An International Practice e-Survey Involving 32 Countries.

PubMed

Saghatchian, Mahasti; Fadoukhair, Zouhour; Hofert, Kathrin; Lanoy, Emilie; Mathieu, Marie-Christine; Mazouni, Chafika; Delaloge, Suzette

2016-01-01

World Health Organization classification has identified a dozen rare subtypes accounting for less than 10% of all breast cancers (BC), generally not taken into account in treatment guidelines. We evaluated professionals' attitudes toward decision-making regarding rare BC and consensus guidelines needs. In this international e-survey, 236 BC experts from all specialties were contacted through email to fill an online questionnaire about their practices. Eighty-six experts from 32 countries participated (36%); 50% medical oncologists, 21% surgeons, 17% pathologists, and 12% radiation oncologists. General BC care decisions were based on consensus guidelines in 77% of expert, whereas routine individual treatment decisions for BC were made by multi-disciplinary boards in 76%. Only 10% strongly considered rare BC should be treated following existing standard guidelines. Interestingly, 50-80% described individualizing treatment for rare BC according to pathologic subtype. More than 90% of experts would welcome international recommendations for rare BC. This large scale international multi-disciplinary survey revealed overarching concerns centered on several key themes: the lack of resources and data to address these less common BC; the heterogeneous management of rare BC depending on geographical location and specialist training; the demand for international consensus guidelines regarding their diagnosis and treatment. © 2015 Wiley Periodicals, Inc.

Knowing when not to swing: EEG evidence that enhanced perception-action coupling underlies baseball batter expertise.

PubMed

Muraskin, Jordan; Sherwin, Jason; Sajda, Paul

2015-12-01

Given a decision that requires less than half a second for evaluating the characteristics of the incoming pitch and generating a motor response, hitting a baseball potentially requires unique perception-action coupling to achieve high performance. We designed a rapid perceptual decision-making experiment modeled as a Go/No-Go task yet tailored to reflect a real scenario confronted by a baseball hitter. For groups of experts (Division I baseball players) and novices (non-players), we recorded electroencephalography (EEG) while they performed the task. We analyzed evoked EEG single-trial variability, contingent negative variation (CNV), and pre-stimulus alpha power with respect to the expert vs. novice groups. We found strong evidence for differences in inhibitory processes between the two groups, specifically differential activity in supplementary motor areas (SMA), indicative of enhanced inhibitory control in the expert (baseball player) group. We also found selective activity in the fusiform gyrus (FG) and orbital gyrus in the expert group, suggesting an enhanced perception-action coupling in baseball players that differentiates them from matched controls. In sum, our results show that EEG correlates of decision formation can be used to identify neural markers of high-performance athletes. Copyright © 2015 Elsevier Inc. All rights reserved.

High School Students Debate the Use of Embryonic Stem Cells: The influence of context on decision-making

NASA Astrophysics Data System (ADS)

Molinatti, Grégoire; Girault, Yves; Hammond, Constance

2010-11-01

The present study analyzes decision-making and argumentation by high school students in a debate situation on a socioscientific issue, the use of embryonic stem cells in research and therapy. We tested the influence on the debates of two different contexts. Adolescent students at the high school level in the same grade (mean age 16.4 years) from rural and urban zones of Provence, France, participated in three debate sessions. During the first session, the students listed the background questions they wanted to ask the expert(s). They were also required to identify one or two major issues that would serve as an outline for the future debate. They then discussed these with the expert(s) during the second session and took note of the answers. During this session, the control groups met with a neuroscientist whereas the experimental 'contextualized' group met with the same neuroscientist together with a representative of an association of patients suffering from a neurodegenerative disease. Analysis of the students' arguments and decision-making revealed that contextualization introduced dynamism in the students' exchanges: they paid more attention to their peers' arguments and were more motivated to argue their own opinion. However, this type of contextualization may contribute to reinforcing ideology in scientific progress.

An intelligent control and virtual display system for evolutionary space station workstation design

NASA Technical Reports Server (NTRS)

Feng, Xin; Niederjohn, Russell J.; Mcgreevy, Michael W.

1992-01-01

Research and development of the Advanced Display and Computer Augmented Control System (ADCACS) for the space station Body-Ported Cupola Virtual Workstation (BP/VCWS) were pursued. The potential applications were explored of body ported virtual display and intelligent control technology for the human-system interfacing applications is space station environment. The new system is designed to enable crew members to control and monitor a variety of space operations with greater flexibility and efficiency than existing fixed consoles. The technologies being studied include helmet mounted virtual displays, voice and special command input devices, and microprocessor based intelligent controllers. Several research topics, such as human factors, decision support expert systems, and wide field of view, color displays are being addressed. The study showed the significant advantages of this uniquely integrated display and control system, and its feasibility for human-system interfacing applications in the space station command and control environment.

Dual-Use Space Technology Transfer Conference and Exhibition. Volume 1

NASA Technical Reports Server (NTRS)

Krishen, Kumar (Compiler)

1994-01-01

This document contains papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; new ways of doing business; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; ans robotics technologies. More than 77 papers, 20 presentations, and 20 exhibits covering various disciplines were presented b experts from NASA, universities, and industry.

Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline.

PubMed

Harris, Lyndsay N; Ismaila, Nofisat; McShane, Lisa M; Andre, Fabrice; Collyar, Deborah E; Gonzalez-Angulo, Ana M; Hammond, Elizabeth H; Kuderer, Nicole M; Liu, Minetta C; Mennel, Robert G; Van Poznak, Catherine; Bast, Robert C; Hayes, Daniel F

2016-04-01

To provide recommendations on appropriate use of breast tumor biomarker assay results to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer. A literature search and prospectively defined study selection sought systematic reviews, meta-analyses, randomized controlled trials, prospective-retrospective studies, and prospective comparative observational studies published from 2006 through 2014. Outcomes of interest included overall survival and disease-free or recurrence-free survival. Expert panel members used informal consensus to develop evidence-based guideline recommendations. The literature search identified 50 relevant studies. One randomized clinical trial and 18 prospective-retrospective studies were found to have evaluated the clinical utility, as defined by the guideline, of specific biomarkers for guiding decisions on the need for adjuvant systemic therapy. No studies that met guideline criteria for clinical utility were found to guide choice of specific treatments or regimens. In addition to estrogen and progesterone receptors and human epidermal growth factor receptor 2, the panel found sufficient evidence of clinical utility for the biomarker assays Oncotype DX, EndoPredict, PAM50, Breast Cancer Index, and urokinase plasminogen activator and plasminogen activator inhibitor type 1 in specific subgroups of breast cancer. No biomarker except for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 was found to guide choices of specific treatment regimens. Treatment decisions should also consider disease stage, comorbidities, and patient preferences. © 2016 by American Society of Clinical Oncology.

Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline

PubMed Central

Harris, Lyndsay N.; McShane, Lisa M.; Andre, Fabrice; Collyar, Deborah E.; Gonzalez-Angulo, Ana M.; Hammond, Elizabeth H.; Kuderer, Nicole M.; Liu, Minetta C.; Mennel, Robert G.; Van Poznak, Catherine; Bast, Robert C.; Hayes, Daniel F.

2016-01-01

Purpose To provide recommendations on appropriate use of breast tumor biomarker assay results to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer. Methods A literature search and prospectively defined study selection sought systematic reviews, meta-analyses, randomized controlled trials, prospective-retrospective studies, and prospective comparative observational studies published from 2006 through 2014. Outcomes of interest included overall survival and disease-free or recurrence-free survival. Expert panel members used informal consensus to develop evidence-based guideline recommendations. Results The literature search identified 50 relevant studies. One randomized clinical trial and 18 prospective-retrospective studies were found to have evaluated the clinical utility, as defined by the guideline, of specific biomarkers for guiding decisions on the need for adjuvant systemic therapy. No studies that met guideline criteria for clinical utility were found to guide choice of specific treatments or regimens. Recommendations In addition to estrogen and progesterone receptors and human epidermal growth factor receptor 2, the panel found sufficient evidence of clinical utility for the biomarker assays Oncotype DX, EndoPredict, PAM50, Breast Cancer Index, and urokinase plasminogen activator and plasminogen activator inhibitor type 1 in specific subgroups of breast cancer. No biomarker except for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 was found to guide choices of specific treatment regimens. Treatment decisions should also consider disease stage, comorbidities, and patient preferences. PMID:26858339

When do we believe experts? The power of the unorthodox view.

PubMed

Alison, Laurence; Almond, Louise; Christiansen, Paul; Waring, Sara; Power, Nicola; Villejoubert, Gaëlle

2012-01-01

This paper examines the extent to which orthodoxy (degree of typicality) and congruence (degree of similarity with own opinion) mediate the influence of expert advice on decision makers' judgments. Overall, 227 members of the public and 60 police officers completed an online questionnaire involving an investigation into a child sex offence. Participants were asked to first (i) formulate their own "profile" of a likely offender then (ii) estimate the guilt of two presented suspect descriptions (orthodox vs. unorthodox), and, following the presentation of an "expert's" profile that matched either the orthodox or the unorthodox suspect, (iii) re-evaluate their guilt judgments of the two suspects based on this new advice. Finally, (iv) the perceived similarity (congruence) between the participants' own and the expert profile was assessed. Results revealed two key findings. First, expert profiles that matched a suspect's description elevated perceptions of guilt in that suspect, whilst also, simultaneously, very significantly decreasing the perception of guilt of the alternative suspect. This suggests a powerful rejection and downward revision of the other suspect. Second, perceived similarity of the profile (to one's own profile) was only a significant factor in increasing guilt judgments when assigning guilt to the unorthodox (as opposed to orthodox) suspect. Comparisons of lay judgments with those of police officers revealed few significant differences in effects. The finding that advice is most influential when unorthodox and incongruent suggests that decision makers are more likely to reevaluate judgments when expert advice contributes novel information that contradicts their beliefs. The practical implications of these findings are discussed for profilers, police, and decision research in general. Copyright © 2012 John Wiley & Sons, Ltd.

FIESTA: An operational decision aid for space network fault isolation

NASA Technical Reports Server (NTRS)

Lowe, Dawn; Quillin, Bob; Matteson, Nadine; Wilkinson, Bill; Miksell, Steve

1987-01-01

The Fault Tolerance Expert System for Tracking and Data Relay Satellite System (TDRSS) Applications (FIESTA) is a fault detection and fault diagnosis expert system being developed as a decision aid to support operations in the Network Control Center (NCC) for NASA's Space Network. The operational objectives which influenced FIESTA development are presented and an overview of the architecture used to achieve these goals are provided. The approach to the knowledge engineering effort and the methodology employed are also presented and illustrated with examples drawn from the FIESTA domain.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Offside Decisions by Expert Assistant Referees in Association Football: Perception and Recall of Spatial Positions in Complex Dynamic Events

ERIC Educational Resources Information Center

Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan

2008-01-01

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Federation Internationale de Football Association (FIFA; n = 29)…

An E-health solution for automatic sleep classification according to Rechtschaffen and Kales: validation study of the Somnolyzer 24 x 7 utilizing the Siesta database.

PubMed

Anderer, Peter; Gruber, Georg; Parapatics, Silvia; Woertz, Michael; Miazhynskaia, Tatiana; Klosch, Gerhard; Saletu, Bernd; Zeitlhofer, Josef; Barbanoj, Manuel J; Danker-Hopfe, Heidi; Himanen, Sari-Leena; Kemp, Bob; Penzel, Thomas; Grozinger, Michael; Kunz, Dieter; Rappelsberger, Peter; Schlogl, Alois; Dorffner, Georg

2005-01-01

To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 x 7) consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20-95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen's kappa: 0.72) between the Somnolyzer 24 x 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 x 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 x 7 and demonstrated its applicability in clinical routine and sleep studies.

Artificial intelligence - New tools for aerospace project managers

NASA Technical Reports Server (NTRS)

Moja, D. C.

1985-01-01

Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1990-01-01

The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

Expert Behavior in Children's Video Game Play.

ERIC Educational Resources Information Center

VanDeventer, Stephanie S.; White, James A.

2002-01-01

Investigates the display of expert behavior by seven outstanding video game-playing children ages 10 and 11. Analyzes observation and debriefing transcripts for evidence of self-monitoring, pattern recognition, principled decision making, qualitative thinking, and superior memory, and discusses implications for educators regarding the development…

NASA's Software Bank (CLIPS)

NASA Technical Reports Server (NTRS)

1992-01-01

C Language Integrated Production System (CLIPS) was used by Esse Systems to develop an expert system for clients who want to automate portions of their operations. The resulting program acts as a scheduling expert and automates routine, repetitive scheduling decisions, allowing employees to spend time on more creative projects.

Knowledge Engineering as a Component of the Curriculum for Medical Cybernetists.

PubMed

Karas, Sergey; Konev, Arthur

2017-01-01

According to a new state educational standard, students who have chosen medical cybernetics as their major must develop a knowledge engineering competency. Previously, in the course "Clinical cybernetics" while practicing project-based learning students were designing automated workstations for medical personnel using client-server technology. The purpose of the article is to give insight into the project of a new educational module "Knowledge engineering". Students will acquire expert knowledge by holding interviews and conducting surveys, and then they will formalize it. After that, students will form declarative expert knowledge in a network model and analyze the knowledge graph. Expert decision making methods will be applied in software on the basis of a production model of knowledge. Project implementation will result not only in the development of analytical competencies among students, but also creation of a practically useful expert system based on student models to support medical decisions. Nowadays, this module is being tested in the educational process.

Comparison of Decision Assist and Clinical Judgment of Experts for Prediction of Lifesaving Interventions

DTIC Science & Technology

2015-03-01

min of pulse oximeter photopletysmograph waveforms and extracted features to predict LSIs. We compared this with clinical judgment of LSIs by...Curve (AUROC). We obtained clinical judgment of need for LSI from 405 expert clinicians in135 trauma patients. The pulse oximeter algorithm...15 min of pulse oximeter waveforms predicts the need for LSIs during initial trauma resuscitation as accurately as judgment of expert trauma

Energizing Government Decision-Makers with the Facts on Solar Technology, Policy, and Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

The Solar Technical Assistance Team (STAT) is a network of solar technology and implementation experts who provide timely, unbiased expertise to assist policymakers and regulators in making informed decisions about solar programs and policies. Government officials can submit requests directly to the STAT for technical assistance. STAT then partners with experts in solar policy, regulation, finance, technology, and other areas to deliver accurate, up-to-date information to state and local decision makers. The STAT responds to requests on a wide range of issues -- including, but not limited to, feed-in tariffs, renewable portfolio standards, rate design, program design, workforce and economicmore » impacts of solar on jurisdictions, and project financing.« less

Rapid Assessment of Ecosystem Service Co-Benefits of Biodiversity Priority Areas in Madagascar

PubMed Central

Andriamaro, Luciano; Cano, Carlos Andres; Grantham, Hedley S.; Hole, David; Juhn, Daniel; McKinnon, Madeleine; Rasolohery, Andriambolantsoa; Steininger, Marc; Wright, Timothy Max

2016-01-01

The importance of ecosystems for supporting human well-being is increasingly recognized by both the conservation and development sectors. Our ability to conserve ecosystems that people rely on is often limited by a lack of spatially explicit data on the location and distribution of ecosystem services (ES), the benefits provided by nature to people. Thus there is a need to map ES to guide conservation investments, to ensure these co-benefits are maintained. To target conservation investments most effectively, ES assessments must be rigorous enough to support conservation planning, rapid enough to respond to decision-making timelines, and often must rely on existing data. We developed a framework for rapid spatial assessment of ES that relies on expert and stakeholder consultation, available data, and spatial analyses in order to rapidly identify sites providing multiple benefits. We applied the framework in Madagascar, a country with globally significant biodiversity and a high level of human dependence on ecosystems. Our objective was to identify the ES co-benefits of biodiversity priority areas in order to guide the investment strategy of a global conservation fund. We assessed key provisioning (fisheries, hunting and non-timber forest products, and water for domestic use, agriculture, and hydropower), regulating (climate mitigation, flood risk reduction and coastal protection), and cultural (nature tourism) ES. We also conducted multi-criteria analyses to identify sites providing multiple benefits. While our approach has limitations, including the reliance on proximity-based indicators for several ES, the results were useful for targeting conservation investments by the Critical Ecosystem Partnership Fund (CEPF). Because our approach relies on available data, standardized methods for linking ES provision to ES use, and expert validation, it has the potential to quickly guide conservation planning and investment decisions in other data-poor regions. PMID:28006005

Application fuzzy multi-attribute decision analysis method to prioritize project success criteria

NASA Astrophysics Data System (ADS)

Phong, Nguyen Thanh; Quyen, Nguyen Le Hoang Thuy To

2017-11-01

Project success is a foundation for project owner to manage and control not only for the current project but also for future potential projects in construction companies. However, identifying the key success criteria for evaluating a particular project in real practice is a challenging task. Normally, it depends on a lot of factors, such as the expectation of the project owner and stakeholders, triple constraints of the project (cost, time, quality), and company's mission, vision, and objectives. Traditional decision-making methods for measuring the project success are usually based on subjective opinions of panel experts, resulting in irrational and inappropriate decisions. Therefore, this paper introduces a multi-attribute decision analysis method (MADAM) for weighting project success criteria by using fuzzy Analytical Hierarchy Process approach. It is found that this method is useful when dealing with imprecise and uncertain human judgments in evaluating project success criteria. Moreover, this research also suggests that although cost, time, and quality are three project success criteria projects, the satisfaction of project owner and acceptance of project stakeholders with the completed project criteria is the most important criteria for project success evaluation in Vietnam.

Accelerated Training at Mach 20: A Brief Communication Submitted from the International Space Station

NASA Technical Reports Server (NTRS)

Foale, C. Michael; Kaleri, Alexander Y.; Sargsyan, Ashot E.; Hamilton, Douglas R.; Melton, Shannon; Martin, David; Dulchavsky, Scott A.

2004-01-01

The performance of complex tasks on the International Space Station (ISS) requires significant preflight crew training commitments and frequent skill and knowledge refreshment. This report documents a recently developed just-in-time training methodology, which integrates preflight hardware familiarization and procedure training with an on-orbit CD-ROM-based skill enhancement. This just-in-time concept was used to support real-time remote expert guidance to complete medical examinations using the ISS Human Research Facility (HRF). An American and Russian ISS crewmember received 2-hours of hands on ultrasound training 8 months prior to the on-orbit ultrasound exam. A CD-ROM-based Onboard Proficiency Enhancement (OPE) interactive multimedia program consisting of memory enhancing tutorials, and skill testing exercises, was completed by the crewmember six days prior to the on-orbit ultrasound exam. The crewmember was then remotely guided through a thoracic, vascular, and echocardiographic examination by ultrasound imaging experts. Results of the CD ROM based OPE session were used to modify the instructions during a complete 35 minute real-time thoracic, cardiac, and carotid/jugular ultrasound study. Following commands from the ground-based expert, the crewmember acquired all target views and images without difficulty. The anatomical content and fidelity of ultrasound video were excellent and adequate for clinical decision-making. Complex ultrasound experiments with expert guidance were performed with high accuracy following limited pre-flight training and CD-ROM-based in-flight review, despite a 2-second communication latency. In-flight application of multimedia proficiency enhancement software, coupled with real-time remote expert guidance, can facilitate the performance of complex demanding tasks.

Leveraging Health Care Simulation Technology for Human Factors Research: Closing the Gap Between Lab and Bedside.

PubMed

Deutsch, Ellen S; Dong, Yue; Halamek, Louis P; Rosen, Michael A; Taekman, Jeffrey M; Rice, John

2016-11-01

We describe health care simulation, designed primarily for training, and provide examples of how human factors experts can collaborate with health care professionals and simulationists-experts in the design and implementation of simulation-to use contemporary simulation to improve health care delivery. The need-and the opportunity-to apply human factors expertise in efforts to achieve improved health outcomes has never been greater. Health care is a complex adaptive system, and simulation is an effective and flexible tool that can be used by human factors experts to better understand and improve individual, team, and system performance within health care. Expert opinion is presented, based on a panel delivered during the 2014 Human Factors and Ergonomics Society Health Care Symposium. Diverse simulators, physically or virtually representing humans or human organs, and simulation applications in education, research, and systems analysis that may be of use to human factors experts are presented. Examples of simulation designed to improve individual, team, and system performance are provided, as are applications in computational modeling, research, and lifelong learning. The adoption or adaptation of current and future training and assessment simulation technologies and facilities provides opportunities for human factors research and engineering, with benefits for health care safety, quality, resilience, and efficiency. Human factors experts, health care providers, and simulationists can use contemporary simulation equipment and techniques to study and improve health care delivery. © 2016, Human Factors and Ergonomics Society.

Guidance for contact tracing of cases of Lassa fever, Ebola or Marburg haemorrhagic fever on an airplane: results of a European expert consultation.

PubMed

Gilsdorf, Andreas; Morgan, Dilys; Leitmeyer, Katrin

2012-11-21

Travel from countries where viral haemorrhagic fevers (VHF) are endemic has increased significantly over the past decades. In several reported VHF events on airplanes, passenger trace back was initiated but the scale of the trace back differed considerably. The absence of guidance documents to help the decision on necessity and scale of the trace back contributed to this variation.This article outlines the recommendations of an expert panel on Lassa fever, Ebola and Marburg haemorrhagic fever to the wider scientific community in order to advise the relevant stakeholders in the decision and scale of a possible passenger trace back. The evidence was collected through review of published literature and through the views of an expert panel. The guidance was agreed by consensus. Only a few events of VHF cases during air travel are reported in literature, with no documented infection in followed up contacts, so that no evidence of transmission of VHF during air travel exists to date. Based on this and the expert opinion, it was recommended that passenger trace back was undertaken only if: the index case had symptoms during the flight; the flight was within 21 days after detection of the event; and for Lassa fever if exposure of body fluid has been reported. The trace back should only be done after confirmation of the index case. Passengers and crew with direct contact, seat neighbours (+/- 1 seat), crew and cleaning personal of the section of the index case should be included in the trace back. No evidence has been found for the transmission of VHF in airplanes. This information should be taken into account, when a trace back decision has to be taken, because such a measure produces an enormous work load. The procedure suggested by the expert group can guide decisions made in future events, where a patient with suspected VHF infection travelled on a plane. However, the actual decision on start and scale of a trace back always lies in the hands of the responsible people taking all relevant information into account.

Guidance for contact tracing of cases of Lassa fever, Ebola or Marburg haemorrhagic fever on an airplane: results of a European expert consultation

PubMed Central

2012-01-01

Background Travel from countries where viral haemorrhagic fevers (VHF) are endemic has increased significantly over the past decades. In several reported VHF events on airplanes, passenger trace back was initiated but the scale of the trace back differed considerably. The absence of guidance documents to help the decision on necessity and scale of the trace back contributed to this variation. This article outlines the recommendations of an expert panel on Lassa fever, Ebola and Marburg haemorrhagic fever to the wider scientific community in order to advise the relevant stakeholders in the decision and scale of a possible passenger trace back. Method The evidence was collected through review of published literature and through the views of an expert panel. The guidance was agreed by consensus. Results Only a few events of VHF cases during air travel are reported in literature, with no documented infection in followed up contacts, so that no evidence of transmission of VHF during air travel exists to date. Based on this and the expert opinion, it was recommended that passenger trace back was undertaken only if: the index case had symptoms during the flight; the flight was within 21 days after detection of the event; and for Lassa fever if exposure of body fluid has been reported. The trace back should only be done after confirmation of the index case. Passengers and crew with direct contact, seat neighbours (+/− 1 seat), crew and cleaning personal of the section of the index case should be included in the trace back. Conclusion No evidence has been found for the transmission of VHF in airplanes. This information should be taken into account, when a trace back decision has to be taken, because such a measure produces an enormous work load. The procedure suggested by the expert group can guide decisions made in future events, where a patient with suspected VHF infection travelled on a plane. However, the actual decision on start and scale of a trace back always lies in the hands of the responsible people taking all relevant information into account. PMID:23170851

Development of a Spacecraft Materials Selector Expert System

NASA Technical Reports Server (NTRS)

Pippin, G.; Kauffman, W. (Technical Monitor)

2002-01-01

This report contains a description of the knowledge base tool and examples of its use. A downloadable version of the Spacecraft Materials Selector (SMS) knowledge base is available through the NASA Space Environments and Effects Program. The "Spacecraft Materials Selector" knowledge base is part of an electronic expert system. The expert system consists of an inference engine that contains the "decision-making" code and the knowledge base that contains the selected body of information. The inference engine is a software package previously developed at Boeing, called the Boeing Expert System Tool (BEST) kit.

Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review

USDA-ARS?s Scientific Manuscript database

Decision-support systems (DDSs) are techniques that help decision makers utilize models to solve problems under complex and uncertain conditions. Predicting conditions that warrant intervention is a key tenet of the concept of integrated pest management (IPM) with the use of expert systems and pest ...

Science and intuition: do both have a place in clinical decision making?

PubMed

Pearson, Helen

Intuition is widely used in clinical decision making yet its use is underestimated compared to scientific decision-making methods. Information processing is used within scientific decision making and is methodical and analytical, whereas intuition relies more on a practitioner's perception. Intuition is an unconscious process and may be referred to as a 'sixth sense', 'hunch' or 'gut feeling'. It is not underpinned by valid and reliable measures. Expert health professionals use a rapid, automatic process to recognise familiar problems instantly. Intuition could therefore involve pattern recognition, where experts draw on experiences, so could be perceived as a cognitive skill rather than a perception or knowing without knowing how. The NHS places great importance on evidence-based practice but intuition is seemingly becoming an acceptable way of thinking and knowing in clinical decision making. Recognising nursing as an art allows intuition to be used and the environment or situation to be interpreted to help inform decision making. Intuition can be used in conjunction with evidence-based practice and to achieve good outcomes and deserves to be acknowledged within clinical practice.

Helping the decision maker effectively promote various experts' views into various optimal solutions to China's institutional problem of health care provider selection through the organization of a pilot health care provider research system.

PubMed

Tang, Liyang

2013-04-04

The main aim of China's Health Care System Reform was to help the decision maker find the optimal solution to China's institutional problem of health care provider selection. A pilot health care provider research system was recently organized in China's health care system, and it could efficiently collect the data for determining the optimal solution to China's institutional problem of health care provider selection from various experts, then the purpose of this study was to apply the optimal implementation methodology to help the decision maker effectively promote various experts' views into various optimal solutions to this problem under the support of this pilot system. After the general framework of China's institutional problem of health care provider selection was established, this study collaborated with the National Bureau of Statistics of China to commission a large-scale 2009 to 2010 national expert survey (n = 3,914) through the organization of a pilot health care provider research system for the first time in China, and the analytic network process (ANP) implementation methodology was adopted to analyze the dataset from this survey. The market-oriented health care provider approach was the optimal solution to China's institutional problem of health care provider selection from the doctors' point of view; the traditional government's regulation-oriented health care provider approach was the optimal solution to China's institutional problem of health care provider selection from the pharmacists' point of view, the hospital administrators' point of view, and the point of view of health officials in health administration departments; the public private partnership (PPP) approach was the optimal solution to China's institutional problem of health care provider selection from the nurses' point of view, the point of view of officials in medical insurance agencies, and the health care researchers' point of view. The data collected through a pilot health care provider research system in the 2009 to 2010 national expert survey could help the decision maker effectively promote various experts' views into various optimal solutions to China's institutional problem of health care provider selection.

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Assessing social and economic effects of perceived risk: Workshop summary: Draft: BWIP Repository Project. [Basalt Waste Isolation Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nealey, S.M.; Liebow, E.B.

1988-03-01

The US Department of Energy sponsored a one-day workshop to discuss the complex dimensions of risk judgment formation and the assessment of social and economic effects of risk perceptions related to the permanent underground storage of highly radioactive waste from commercial nuclear power plants. Affected parties have publicly expressed concerns about potentially significant risk-related effects of this approach to waste management. A selective review of relevant literature in psychology, decision analysis, economics, sociology, and anthropology was completed, along with an examination of decision analysis techniques that might assist in developing suitable responses to public risk-related concerns. The workshop was organizedmore » as a forum in which a set of distinguished experts could exchange ideas and observations about the problems of characterizing the effects of risk judgments. Out of the exchange emerged the issues or themes of problems with probabilistic risk assessment techniques are evident; differences exist in the way experts and laypersons view risk, and this leads to higher levels of public concern than experts feel are justified; experts, risk managers, and decision-makers sometimes err in assessing risk and in dealing with the public; credibility and trust are important contributing factors in the formation of risk judgments; social and economic consequences of perceived risk should be properly anticipated; improvements can be made in informing the public about risk; the role of the public in risk assessment, risk management and decisions about risk should be reconsidered; and mitigation and compensation are central to resolving conflicts arising from divergent risk judgments. 1 tab.« less

Patients' ratings of genetic conditions validate a taxonomy to simplify decisions about preconception carrier screening via genome sequencing.

PubMed

Leo, Michael C; McMullen, Carmit; Wilfond, Benjamin S; Lynch, Frances L; Reiss, Jacob A; Gilmore, Marian J; Himes, Patricia; Kauffman, Tia L; Davis, James V; Jarvik, Gail P; Berg, Jonathan S; Harding, Cary; Kennedy, Kathleen A; Simpson, Dana Kostiner; Quigley, Denise I; Richards, C Sue; Rope, Alan F; Goddard, Katrina A B

2016-03-01

Advances in genome sequencing and gene discovery have created opportunities to efficiently assess more genetic conditions than ever before. Given the large number of conditions that can be screened, the implementation of expanded carrier screening using genome sequencing will require practical methods of simplifying decisions about the conditions for which patients want to be screened. One method to simplify decision making is to generate a taxonomy based on expert judgment. However, expert perceptions of condition attributes used to classify these conditions may differ from those used by patients. To understand whether expert and patient perceptions differ, we asked women who had received preconception genetic carrier screening in the last 3 years to fill out a survey to rate the attributes (predictability, controllability, visibility, and severity) of several autosomal recessive or X-linked genetic conditions. These conditions were classified into one of five taxonomy categories developed by subject experts (significantly shortened lifespan, serious medical problems, mild medical problems, unpredictable medical outcomes, and adult-onset conditions). A total of 193 women provided 739 usable ratings across 20 conditions. The mean ratings and correlations demonstrated that participants made distinctions across both attributes and categories. Aggregated mean attribute ratings across categories demonstrated logical consistency between the key features of each attribute and category, although participants perceived little difference between the mild and serious categories. This study provides empirical evidence for the validity of our proposed taxonomy, which will simplify patient decisions for results they would like to receive from preconception carrier screening via genome sequencing. © 2016 Wiley Periodicals, Inc.

The utility of case formulation in treatment decision making; the effect of experience and expertise.

PubMed

Dudley, Robert; Ingham, Barry; Sowerby, Katy; Freeston, Mark

2015-09-01

We examined whether case formulation guides the endorsement of appropriate treatment strategies. We also considered whether experience and training led to more effective treatment decisions. To examine these questions two related studies were conducted both of which used a novel paradigm using clinically relevant decision-making tasks with multiple sources of information. Study one examined how clinicians utilised a pre-constructed CBT case formulation to plan treatment. Study two utilised a clinician-generated formulation to further examine the process of formulation development and the impact on treatment planning. Both studies considered the effect of therapist experience. Both studies indicated that clinicians used the case formulation to select treatment choices that were highly matched to the case as described in the vignette. However, differences between experts and novice clinicians were only demonstrated when clinicians developed their own formulations of case material. When they developed their own formulations the experts' formulations were more parsimonious, internally consistent, and contained fewer errors and the experts were less swayed by irrelevant treatment options. The nature of the experimental task, involving ratings of suitability of possible treatment options suggested for the case, limits the interpretation that formulation directs the development or generation of the clinician's treatment plan. In study two the task may still have limited the capacity to demonstrate further differences between expert and novice therapists. Formulation helps guide certain aspects of effective treatment decision making. When asked to generate a formulation clinicians with greater experience and expertise do this more effectively. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests.

PubMed

Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A

2015-10-01

Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Decision making.

PubMed

Chambers, David W

2011-01-01

A decision is a commitment of resources under conditions of risk in expectation of the best future outcome. The smart decision is always the strategy with the best overall expected value-the best combination of facts and values. Some of the special circumstances involved in decision making are discussed, including decisions where there are multiple goals, those where more than one person is involved in making the decision, using trigger points, framing decisions correctly, commitments to lost causes, and expert decision makers. A complex example of deciding about removal of asymptomatic third molars, with and without an EBD search, is discussed.

Visualization support for risk-informed decision making when planning and managing software developments

NASA Technical Reports Server (NTRS)

Feather, Martin S.; Kiper, James D.; Menzies, Tim

2005-01-01

Key decisions are made in the early stages of planning and management of software developments. The information basis for these decisions is often a mix of analogy with past developments, and the best judgments of domain experts. Visualization of this information can support to such decision making by clarifying the status of the information and yielding insights into the ramifications of that information vis-a-vis decision alternatives.

Evolutionary Algorithm Based Automated Reverse Engineering and Defect Discovery

DTIC Science & Technology

2007-09-21

a previous application of a GP as a data mining function to evolve fuzzy decision trees symbolically [3-5], the terminal set consisted of fuzzy...of input and output information is required. In the case of fuzzy decision trees, the database represented a collection of scenarios about which the...fuzzy decision tree to be evolved would make decisions . The database also had entries created by experts representing decisions about the scenarios

Empirical evaluation of decision support systems: Needs, definitions, potential methods, and an example pertaining to waterfowl management

USGS Publications Warehouse

Sojda, R.S.

2007-01-01

Decision support systems are often not empirically evaluated, especially the underlying modelling components. This can be attributed to such systems necessarily being designed to handle complex and poorly structured problems and decision making. Nonetheless, evaluation is critical and should be focused on empirical testing whenever possible. Verification and validation, in combination, comprise such evaluation. Verification is ensuring that the system is internally complete, coherent, and logical from a modelling and programming perspective. Validation is examining whether the system is realistic and useful to the user or decision maker, and should answer the question: “Was the system successful at addressing its intended purpose?” A rich literature exists on verification and validation of expert systems and other artificial intelligence methods; however, no single evaluation methodology has emerged as preeminent. At least five approaches to validation are feasible. First, under some conditions, decision support system performance can be tested against a preselected gold standard. Second, real-time and historic data sets can be used for comparison with simulated output. Third, panels of experts can be judiciously used, but often are not an option in some ecological domains. Fourth, sensitivity analysis of system outputs in relation to inputs can be informative. Fifth, when validation of a complete system is impossible, examining major components can be substituted, recognizing the potential pitfalls. I provide an example of evaluation of a decision support system for trumpeter swan (Cygnus buccinator) management that I developed using interacting intelligent agents, expert systems, and a queuing system. Predicted swan distributions over a 13-year period were assessed against observed numbers. Population survey numbers and banding (ringing) studies may provide long term data useful in empirical evaluation of decision support.

Health literacy skills for informed decision making in colorectal cancer screening: Perceptions of screening invitees and experts.

PubMed

Woudstra, Anke J; Timmermans, Daniëlle R M; Uiters, Ellen; Dekker, Evelien; Smets, Ellen M A; Fransen, Mirjam P

2018-06-01

The process of informed decision making (IDM) requires an adequate level of health literacy. To ensure that all individuals have equal opportunity to make an informed decision in colorectal cancer (CRC) screening, it is essential to gain more insight into which health literacy skills are needed for IDM. Our aims were (i) to explore how individuals make a decision about CRC screening and (ii) to explore which skills are needed for IDM in CRC screening and (iii) to integrate these findings within a conceptual framework. We conducted 3 focus groups with individuals eligible for CRC screening (n = 22) and 2 focus groups with experts in the field of health literacy, oncology and decision making, including scientific researchers and health-care professionals (n = 17). We used framework analysis to analyse our data. We identified and specified ten health literacy skills, which varied from the ability to read and understand CRC screening information to the ability to weigh up pros and cons of screening for personal relevance. The skills were linked to 8 decision-making stages in CRC screening within a conceptual framework. We found differences in perceptions between screening invitees and experts, especially in the perceived importance of CRC screening information for IDM. This study provides insight into the decision-making stages and health literacy skills that are essential for IDM in CRC screening. The proposed conceptual framework can be used to inform the development of context-based measurement of health literacy and interventions to support IDM in cancer screening. © 2017 The Authors Health Expectations published by John Wiley & Sons Ltd.

Decision Making in Armored Platoon Command

DTIC Science & Technology

1990-07-01

throughout the study, the Critical Decision method was again useful. We applied it differently in this study, focusing more on situational awareness...Additional work with the Critical Decision method may provide the sharpest insights into the nature of expert-novice differences in real world settings...cwre contrasted to traditional decision--akinL ’ I iteca-turo. Training methods were recommended that would in- corporate the i:mplications of the

Improving Human Resources for Health means Retaining Health-Workers: Application of the WHO-Recommendations for the Retention of Health-Workers in Rural Northern-Nigeria.

PubMed

Afenyadu, Godwin Y; Adegoke, Adetoro A; Findley, Sally

2017-01-01

Nigeria is one of 57 countries with critical shortage of health workers (HWs). Strategies to increase and equitably distribute HWs are critical to the achievement of Health Millennium/Sustainable Development Goals. We describe how three Northern Nigeria states adapted World Health Organisation (WHO)-recommended incentives to attract, recruit, and retain midwives. Secondary analysis of data from two surveys assessing midwife motivation, retention, and attrition in Northern Nigeria; and expert consultations. Midwives highlighted financial and non-financial incentives as key factors in their decisions to renew their contracts. Their perspectives informed the consensus positions of health managers, policymakers and heads of institutions, and led to the adaptation of the WHO recommendations into appropriate state-specific incentive packages. The feedback from midwives combined with an expert consultation approach allowed stakeholders to consider and use available evidence to select appropriate incentive packages that offer the greatest potential for helping to address inadequate numbers of rural midwives.

Verification and Validation of KBS with Neural Network Components

NASA Technical Reports Server (NTRS)

Wen, Wu; Callahan, John

1996-01-01

Artificial Neural Network (ANN) play an important role in developing robust Knowledge Based Systems (KBS). The ANN based components used in these systems learn to give appropriate predictions through training with correct input-output data patterns. Unlike traditional KBS that depends on a rule database and a production engine, the ANN based system mimics the decisions of an expert without specifically formulating the if-than type of rules. In fact, the ANNs demonstrate their superiority when such if-then type of rules are hard to generate by human expert. Verification of traditional knowledge based system is based on the proof of consistency and completeness of the rule knowledge base and correctness of the production engine.These techniques, however, can not be directly applied to ANN based components.In this position paper, we propose a verification and validation procedure for KBS with ANN based components. The essence of the procedure is to obtain an accurate system specification through incremental modification of the specifications using an ANN rule extraction algorithm.

The role of experts in postaccident recovery: lessons learnt from Chernobyl and Fukushima.

PubMed

Gariel, J C; Rollinger, F; Schneider, T

2018-01-01

Following a nuclear accident, a major dilemma for affected people is whether to stay or leave the affected area, or, for those who have been evacuated, whether or not to return to the decontaminated zones. Populations who have to make such decisions have to consider many parameters, one of which is the radiological situation. Feedback from Chernobyl and Fukushima has demonstrated that involvement and empowerment of the affected population is a way to provide them with the necessary elements to make informed decisions and, if they decide to return to decontaminated areas, to minimise exposure by contributing to the development of a prudent attitude and vigilance towards exposure. However, involving stakeholders in postaccident management raises the question of the role of experts and public authorities in supporting the inhabitants who have to make decisions about their future. Based on experiences in Chernobyl and Fukushima, this paper will discuss various principles that have to be taken into account by experts and public authorities about their role and position when dealing with stakeholders in a postaccident recovery process.

Building a Foreign Military Sales Construction Delivery Strategy Decision Support System

DTIC Science & Technology

1991-09-01

DSS, formulates it into a computer model and produces solutions using information and expert heuristics. Using the Expert Systeic Process to Build a DSS...computer model . There are five stages in the development of an expert system. They are: 1) Identify and characterize the important aspects of the problem...and Steven A. Hidreth. U.S. Security Assistance: The Political Process. Massachusetts: Heath and Company, 1985. 19. Guirguis , Amir A., Program

Spatial Bayesian belief networks as a planning decision tool for mapping ecosystem services trade-offs on forested landscapes.

PubMed

Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro

2016-01-01

An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas. Copyright © 2015 Elsevier Inc. All rights reserved.

A web-based neurological pain classifier tool utilizing Bayesian decision theory for pain classification in spinal cord injury patients

NASA Astrophysics Data System (ADS)

Verma, Sneha K.; Chun, Sophia; Liu, Brent J.

2014-03-01

Pain is a common complication after spinal cord injury with prevalence estimates ranging 77% to 81%, which highly affects a patient's lifestyle and well-being. In the current clinical setting paper-based forms are used to classify pain correctly, however, the accuracy of diagnoses and optimal management of pain largely depend on the expert reviewer, which in many cases is not possible because of very few experts in this field. The need for a clinical decision support system that can be used by expert and non-expert clinicians has been cited in literature, but such a system has not been developed. We have designed and developed a stand-alone tool for correctly classifying pain type in spinal cord injury (SCI) patients, using Bayesian decision theory. Various machine learning simulation methods are used to verify the algorithm using a pilot study data set, which consists of 48 patients data set. The data set consists of the paper-based forms, collected at Long Beach VA clinic with pain classification done by expert in the field. Using the WEKA as the machine learning tool we have tested on the 48 patient dataset that the hypothesis that attributes collected on the forms and the pain location marked by patients have very significant impact on the pain type classification. This tool will be integrated with an imaging informatics system to support a clinical study that will test the effectiveness of using Proton Beam radiotherapy for treating spinal cord injury (SCI) related neuropathic pain as an alternative to invasive surgical lesioning.

Relation of Knowledge and Performance in Boys' Tennis: Age and Expertise.

ERIC Educational Resources Information Center

McPherson, Sue L.; Thomas, Jerry R.

1989-01-01

Examined 10- to 13-year-old boys' development of knowledge structure and sport performance in tennis by comparing skills and knowledge of experts and novices. Experts focused on higher concepts and exhibited greater decision-making ability because of their more highly developed knowledge structure. (SAK)

Experience Does Not Equal Expertise in Recognizing Infrequent Incoming Gunfire: Neural Markers for Experience and Task Expertise at Peak Behavioral Performance

PubMed Central

Sherwin, Jason Samuel; Gaston, Jeremy Rodney

2015-01-01

For a soldier, decisions to use force can happen rapidly and sometimes lead to undesired consequences. In many of these situations, there is a rapid assessment by the shooter that recognizes a threat and responds to it with return fire. But the neural processes underlying these rapid decisions are largely unknown, especially amongst those with extensive weapons experience and expertise. In this paper, we investigate differences in weapons experts and non-experts during an incoming gunfire detection task. Specifically, we analyzed the electroencephalography (EEG) of eleven expert marksmen/soldiers and eleven non-experts while they listened to an audio scene consisting of a sequence of incoming and non-incoming gunfire events. Subjects were tasked with identifying each event as quickly as possible and committing their choice via a motor response. Contrary to our hypothesis, experts did not have significantly better behavioral performance or faster response time than novices. Rather, novices indicated trends of better behavioral performance than experts. These group differences were more dramatic in the EEG correlates of incoming gunfire detection. Using machine learning, we found condition-discriminating EEG activity among novices showing greater magnitude and covering longer periods than those found in experts. We also compared group-level source reconstruction on the maximum discriminating neural correlates and found that each group uses different neural structures to perform the task. From condition-discriminating EEG and source localization, we found that experts perceive more categorical overlap between incoming and non-incoming gunfire. Consequently, the experts did not perform as well behaviorally as the novices. We explain these unexpected group differences as a consequence of experience with gunfire not being equivalent to expertise in recognizing incoming gunfire. PMID:25658335

Economic analyses to support decisions about HPV vaccination in low- and middle-income countries: a consensus report and guide for analysts.

PubMed

Jit, Mark; Levin, Carol; Brisson, Marc; Levin, Ann; Resch, Stephen; Berkhof, Johannes; Kim, Jane; Hutubessy, Raymond

2013-01-30

Low- and middle-income countries need to consider economic issues such as cost-effectiveness, affordability and sustainability before introducing a program for human papillomavirus (HPV) vaccination. However, many such countries lack the technical capacity and data to conduct their own analyses. Analysts informing policy decisions should address the following questions: 1) Is an economic analysis needed? 2) Should analyses address costs, epidemiological outcomes, or both? 3) If costs are considered, what sort of analysis is needed? 4) If outcomes are considered, what sort of model should be used? 5) How complex should the analysis be? 6) How should uncertainty be captured? 7) How should model results be communicated? Selecting the appropriate analysis is essential to ensure that all the important features of the decision problem are correctly represented, but that the analyses are not more complex than necessary. This report describes the consensus of an expert group convened by the World Health Organization, prioritizing key issues to be addressed when considering economic analyses to support HPV vaccine introduction in these countries.

Air Traffic Management Research at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Lee, Katharine

2005-01-01

Since the late 1980's, NASA Ames researchers have been investigating ways to improve the air transportation system through the development of decision support automation. These software advances, such as the Center-TRACON Automation System (eTAS) have been developed with teams of engineers, software developers, human factors experts, and air traffic controllers; some ASA Ames decision support tools are currently operational in Federal Aviation Administration (FAA) facilities and some are in use by the airlines. These tools have provided air traffic controllers and traffic managers the capabilities to help reduce overall delays and holding, and provide significant cost savings to the airlines as well as more manageable workload levels for air traffic service providers. NASA is continuing to collaborate with the FAA, as well as other government agencies, to plan and develop the next generation of decision support tools that will support anticipated changes in the air transportation system, including a projected increase to three times today's air-traffic levels by 2025. The presentation will review some of NASA Ames' recent achievements in air traffic management research, and discuss future tool developments and concepts currently under consideration.

Human matching performance of genuine crime scene latent fingerprints.

PubMed

Thompson, Matthew B; Tangen, Jason M; McCarthy, Duncan J

2014-02-01

There has been very little research into the nature and development of fingerprint matching expertise. Here we present the results of an experiment testing the claimed matching expertise of fingerprint examiners. Expert (n = 37), intermediate trainee (n = 8), new trainee (n = 9), and novice (n = 37) participants performed a fingerprint discrimination task involving genuine crime scene latent fingerprints, their matches, and highly similar distractors, in a signal detection paradigm. Results show that qualified, court-practicing fingerprint experts were exceedingly accurate compared with novices. Experts showed a conservative response bias, tending to err on the side of caution by making more errors of the sort that could allow a guilty person to escape detection than errors of the sort that could falsely incriminate an innocent person. The superior performance of experts was not simply a function of their ability to match prints, per se, but a result of their ability to identify the highly similar, but nonmatching fingerprints as such. Comparing these results with previous experiments, experts were even more conservative in their decision making when dealing with these genuine crime scene prints than when dealing with simulated crime scene prints, and this conservatism made them relatively less accurate overall. Intermediate trainees-despite their lack of qualification and average 3.5 years experience-performed about as accurately as qualified experts who had an average 17.5 years experience. New trainees-despite their 5-week, full-time training course or their 6 months experience-were not any better than novices at discriminating matching and similar nonmatching prints, they were just more conservative. Further research is required to determine the precise nature of fingerprint matching expertise and the factors that influence performance. The findings of this representative, lab-based experiment may have implications for the way fingerprint examiners testify in court, but what the findings mean for reasoning about expert performance in the wild is an open, empirical, and epistemological question.

Methods for optimizing solutions when considering group arguments by team of experts

NASA Astrophysics Data System (ADS)

Chernyi, Sergei; Budnik, Vlad

2017-11-01

The article is devoted to methods of expert evaluation. The technology of expert evaluation is presented from the standpoint of precedent structures. In this paper, an aspect of the mathematical basis for constructing a component of decision analysis is considered. In fact, this approach leaves out any identification of their knowledge and skills of simulating organizational and manufacturing situations and taking efficient managerial decisions; it doesn't enable any identification and assessment of their knowledge on the basis of multi-informational and least loss-making methods and information technologies. Hence the problem is to research and develop a methodology for systemic identification of professional problem-focused knowledge acquired by employees operating adaptive automated systems of training management (AASTM operators), which shall also further the theory and practice of the intelligence-related aspects thereof.

Evaluating neural networks and artificial intelligence systems

NASA Astrophysics Data System (ADS)

Alberts, David S.

1994-02-01

Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.

Eyes on the prize: reflections on the impact of the evolving digital ecology on the librarian as expert intermediary and knowledge coach, 1969-2009.

PubMed

Homan, J Michael

2010-01-01

The 2009 Janet Doe Lecture reflects on the continuing value and increasing return on investment of librarian-mediated services in the constantly evolving digital ecology and complex knowledge environment of the health sciences. The interrelationship of knowledge, decision making based on knowledge, technology used to access and retrieve knowledge, and the important linkage roles of expert librarian intermediaries is examined. Professional experiences from 1969 to 2009, occurring during a time of unprecedented changes in the digital ecology of librarianship, are the base on which the evolving role and value of librarians as knowledge coaches and expert intermediaries are examined. Librarian-mediated services linking knowledge and critical decision making in health care have become more valuable than ever as technology continues to reshape an increasingly complex knowledge environment.

Human judgment vs. quantitative models for the management of ecological resources.

PubMed

Holden, Matthew H; Ellner, Stephen P

2016-07-01

Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost-effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to decisions that harm the environment and economy. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this study, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: (1) the model used to produce the simulated population dynamics observed in the game, with the values of all parameters known (as a control), (2) the same model, but with unknown parameter values that must be estimated during the game from observed data, (3) models that are structurally different from those used to simulate the population dynamics, and (4) a model that ignores age structure. Humans on average performed much worse than the models in cases 1-3, but in a small minority of scenarios, models produced worse outcomes than those resulting from students making decisions based on experience and judgment. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66% of the time. © 2016 by the Ecological Society of America.

Decision support from local data: creating adaptive order menus from past clinician behavior.

PubMed

Klann, Jeffrey G; Szolovits, Peter; Downs, Stephen M; Schadow, Gunther

2014-04-01

Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based Clinical Decision Support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian Network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the Urgent Visit Clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. A short order menu on average contained the next order (weighted average length 3.91-5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714-.844 (depending on domain). However, AUC had high variance (.50-.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an Association Rule Mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. Copyright © 2013 Elsevier Inc. All rights reserved.

Decision Support from Local Data: Creating Adaptive Order Menus from Past Clinician Behavior

PubMed Central

Klann, Jeffrey G.; Szolovits, Peter; Downs, Stephen; Schadow, Gunther

2014-01-01

Objective Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based clinical decision support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. Materials and Methods We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the urgent visit clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. Results A short order menu on average contained the next order (weighted average length 3.91–5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714–.844 (depending on domain). However, AUC had high variance (.50–.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an association rule mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. Discussion and Conclusion This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. PMID:24355978

Principal Investigator-in-a-Box

NASA Technical Reports Server (NTRS)

Young, Laurence R.

1999-01-01

Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal Investigator, and combine that with real-time data available in space in order to advise the astronaut about how to proceed in real time. [PI] advises the astronaut during the progress of an experiment in much the same way a real Principal Investigator might do while looking over the astronaut's shoulder. In its original application, [PI] mimicked several of the tasks of the Principal Investigator, including data quality monitoring, troubleshooting, prescheduling, protocol management and "interesting data" detection. The proposed research focuses on the efficacy of this technique as applied to the data quality monitoring and troubleshooting aspects of [PI].

Web-based health services and clinical decision support.

PubMed

Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

2004-01-01

The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.

A Life-Cycle Cost Estimating Methodology for NASA-Developed Air Traffic Control Decision Support Tools

NASA Technical Reports Server (NTRS)

Wang, Jianzhong Jay; Datta, Koushik; Landis, Michael R. (Technical Monitor)

2002-01-01

This paper describes the development of a life-cycle cost (LCC) estimating methodology for air traffic control Decision Support Tools (DSTs) under development by the National Aeronautics and Space Administration (NASA), using a combination of parametric, analogy, and expert opinion methods. There is no one standard methodology and technique that is used by NASA or by the Federal Aviation Administration (FAA) for LCC estimation of prospective Decision Support Tools. Some of the frequently used methodologies include bottom-up, analogy, top-down, parametric, expert judgement, and Parkinson's Law. The developed LCC estimating methodology can be visualized as a three-dimensional matrix where the three axes represent coverage, estimation, and timing. This paper focuses on the three characteristics of this methodology that correspond to the three axes.

The neural circuitry of expertise: perceptual learning and social cognition

PubMed Central

Harré, Michael

2013-01-01

Amongst the most significant questions we are confronted with today include the integration of the brain's micro-circuitry, our ability to build the complex social networks that underpin society and how our society impacts on our ecological environment. In trying to unravel these issues one place to begin is at the level of the individual: to consider how we accumulate information about our environment, how this information leads to decisions and how our individual decisions in turn create our social environment. While this is an enormous task, we may already have at hand many of the tools we need. This article is intended to review some of the recent results in neuro-cognitive research and show how they can be extended to two very specific and interrelated types of expertise: perceptual expertise and social cognition. These two cognitive skills span a vast range of our genetic heritage. Perceptual expertise developed very early in our evolutionary history and is a highly developed part of all mammals' cognitive ability. On the other hand social cognition is most highly developed in humans in that we are able to maintain larger and more stable long term social connections with more behaviorally diverse individuals than any other species. To illustrate these ideas I will discuss board games as a toy model of social interactions as they include many of the relevant concepts: perceptual learning, decision-making, long term planning and understanding the mental states of other people. Using techniques that have been developed in mathematical psychology, I show that we can represent some of the key features of expertise using stochastic differential equations (SDEs). Such models demonstrate how an expert's long exposure to a particular context influences the information they accumulate in order to make a decision.These processes are not confined to board games, we are all experts in our daily lives through long exposure to the many regularities of daily tasks and social contexts. PMID:24381550

The potential of expert systems for remote sensing application

NASA Technical Reports Server (NTRS)

Mooneyhan, D. W.

1983-01-01

An overview of the status and potential of artificial intelligence-driven expert systems in the role of image data analysis is presented. An expert system is defined and its structure is summarized. Three such systems designed for image interpretation are outlined. The use of an expert system to detect changes on the earth's surface is discussed, and the components of a knowledge-based image interpretation system and their make-up are outlined. An example of how such a system should work for an area in the tropics where deforestation has occurred is presented as a sequence of situation/action decisions.

A CLIPS-based expert system for the evaluation and selection of robots

NASA Technical Reports Server (NTRS)

Nour, Mohamed A.; Offodile, Felix O.; Madey, Gregory R.

1994-01-01

This paper describes the development of a prototype expert system for intelligent selection of robots for manufacturing operations. The paper first develops a comprehensive, three-stage process to model the robot selection problem. The decisions involved in this model easily lend themselves to an expert system application. A rule-based system, based on the selection model, is developed using the CLIPS expert system shell. Data about actual robots is used to test the performance of the prototype system. Further extensions to the rule-based system for data handling and interfacing capabilities are suggested.

Expert knowledge elicitation using computer simulation: the organization of frail elderly case management as an illustration.

PubMed

Chiêm, Jean-Christophe; Van Durme, Thérèse; Vandendorpe, Florence; Schmitz, Olivier; Speybroeck, Niko; Cès, Sophie; Macq, Jean

2014-08-01

Various elderly case management projects have been implemented in Belgium. This type of long-term health care intervention involves contextual factors and human interactions. These underlying complex mechanisms can be usefully informed with field experts' knowledge, which are hard to make explicit. However, computer simulation has been suggested as one possible method of overcoming the difficulty of articulating such elicited qualitative views. A simulation model of case management was designed using an agent-based methodology, based on the initial qualitative research material. Variables and rules of interaction were formulated into a simple conceptual framework. This model has been implemented and was used as a support for a structured discussion with experts in case management. The rigorous formulation provided by the agent-based methodology clarified the descriptions of the interventions and the problems encountered regarding: the diverse network topologies of health care actors in the project; the adaptation time required by the intervention; the communication between the health care actors; the institutional context; the organization of the care; and the role of the case manager and his or hers personal ability to interpret the informal demands of the frail older person. The simulation model should be seen primarily as a tool for thinking and learning. A number of insights were gained as part of a valuable cognitive process. Computer simulation supporting field experts' elicitation can lead to better-informed decisions in the organization of complex health care interventions. © 2013 John Wiley & Sons, Ltd.

Anti-HER2 Therapy Beyond Second-Line for HER2-Positive Metastatic Breast Cancer: A Short Review and Recommendations for Several Clinical Scenarios from a Spanish Expert Panel

PubMed Central

Martínez-Jañez, Noelia; Chacón, Ignacio; de Juan, Ana; Cruz-Merino, Luis; del Barco, Sònia; Fernández, Isaura; García-Teijido, Paula; Gómez-Bernal, Amalia; Plazaola, Arrate; Ponce, José; Servitja, Sonia; Zamora, Pilar

2016-01-01

Summary Background The aim of this project was to provide an expert opinion regarding anti-human epidermal growth factor receptor 2 (HER2) therapy beyond second-line treatment of metastatic breast cancer (mBC). Methods A group of experts discussed specific issues concerning anti-HER2 therapy in late-line settings in mBC. Results Trastuzumab emtansine (T-DM1) or dual HER2 blockade appeared to be good options for HER2-positive mBC after ≥ 2 HER2-targeted therapies. Once an objective response has been achieved with anti-HER2-containing therapy, the anti-HER2 agent can be continued until progression of the disease, unacceptable toxicity or patient decision. mBC treated with ≥ 3 consecutive lines of anti-HER therapy, ≥ 1 being a dual HER2 blockade and with early progression of disease during a fourth or later-line treatment, are clinically resistant to anti-HER therapy. For progression of metastasis in the brain after anti-HER2 therapy, lapatinib and chemotherapy appear to be a good alternative after best local treatment. Conclusions Further clinical trials are needed to provide valuable knowledge about the best treatment options in the later settings of mBC. PMID:27239176

Decision Making in the Airplane

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Shafto, Michael G. (Technical Monitor)

1995-01-01

The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking In response to a problem, This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park

USGS Publications Warehouse

Martin, Julien; Fackler, Paul L.; Nichols, James D.; Runge, Michael C.; McIntyre, Carol L.; Lubow, Bruce L.; McCluskie, Maggie C.; Schmutz, Joel A.

2011-01-01

Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles

Development and application of an innovative expert decision support system to manage sediments and to assess environmental risk in freshwater ecosystems.

PubMed

Dagnino, Alessandro; Bo, Tiziano; Copetta, Andrea; Fenoglio, Stefano; Oliveri, Caterina; Bencivenga, Mauro; Felli, Angelo; Viarengo, Aldo

2013-10-01

With the aim of supporting decision makers to manage contamination in freshwater environments, an innovative expert decision support system (EDSS) was developed. The EDSS was applied in a sediment quality assessment along the Bormida river (NW, Italy) which has been heavily contaminated by an upstream industrial site for more than a century. Sampling sites were classified by means of comparing chemical concentrations with effect-based target values (threshold and probable effect concentrations). The level of each contaminant and the combined toxic pressure were used to rank sites into three categories: (i) uncontaminated (8 sites), (ii) mildly contaminated (4) and (iii) heavily contaminated (19). In heavily contaminated sediments, an environmental risk index (EnvRI) was determined by means of integrating chemical data with ecotoxicological and ecological parameters (triad approach). In addition a sediment risk index (SedRI) was computed from combining chemical and ecotoxicological data. Eight sites exhibited EnvRI values ≥0.25, the safety threshold level (range of EnvRI values: 0.14-0.31) whereas SedRI exceeded the safety threshold level at 6 sites (range of SedRI values: 0.16-0.36). At sites classified as mildly contaminated, sublethal biomarkers were integrated with chemical data into a biological vulnerability index (BVI), which exceeded the safety threshold level at one site (BVI value: 0.28). Finally, potential human risk was assessed in selected stations (11 sites) by integrating genotoxicity biomarkers (GTI index falling in the range 0.00-0.53). General conclusions drawn from the EDSS data include: (i) in sites classified as heavily contaminated, only a few exhibited some significant, yet limited, effects on biodiversity; (ii) restrictions in re-using sediments from heavily contaminated sites found little support in ecotoxicological data; (iii) in the majority of the sites classified as mildly contaminated, tested organisms exhibited low response levels; (iv) preliminary results on genotoxicity biomarkers indicate possible negative consequences for humans if exposed to river sediments from target areas. © 2013.

Expert Baseball Batters Have Greater Sensitivity in Making Swing Decisions

ERIC Educational Resources Information Center

Gray, Rob

2010-01-01

This study used signal detection theory to conceptualize the problem a baseball batter faces when deciding whether or not to swing at a pitch. It examined the launch angle (LA) criteria used by expert (college players) and less experienced (recreational league players) batters using a baseball batting simulation. This study showed that, although…

Changing Perspectives on the Benefits of Newborn Screening

ERIC Educational Resources Information Center

Bailey, Donald B., Jr.; Beskow, Laura M.; Davis, Arlene M.; Skinner, Debra

2006-01-01

The likelihood of benefit is fundamental to decision making about newborn screening. But benefit is construed in different ways by different stakeholders. This article begins with a review of benefit as considered historically by various expert panels and organizations. We then show how 78 conditions fared when experts recently rated them on…

Learning and Decision Making in Groups

ERIC Educational Resources Information Center

Rahimian, M. Amin

2017-01-01

Many important real-world decision-making problems involve group interactions among individuals with purely informational interactions. Such situations arise for example in jury deliberations, expert committees, medical diagnoses, etc. We model the purely informational interactions of group members, where they receive private information and act…

Selective Effects of Sport Expertise on the Stages of Mental Rotation Tasks With Object-Based and Egocentric Transformations

PubMed Central

Feng, Tian; Zhang, Zhongqiu; Ji, Zhiguang; Jia, Binbin; Li, Yawei

2017-01-01

It is well established that motor expertise is linked to superior mental rotation ability, but few studies have attempted to explain the factors that influence the stages of mental rotation in sport experts. Some authors have argued that athletes are faster in the perceptual and decision stages but not in the rotation stages of object-based transformations; however, stimuli related to sport have not been used to test mental rotation with egocentric transformations. Therefore, 24 adolescent elite divers and 23 adolescent nonathletes completed mental rotation tasks with object-based and egocentric transformations. The results showed faster reaction times (RTs) for the motor experts in tasks with both types of transformations (object-based cube, object-based body, and egocentric body). Additionally, the differences in favour of motor experts in the perceptual and decision stages were confirmed. Interestingly, motor experts also outperformed nonathletes in the rotation stages in the egocentric transformations. These findings are discussed against the background of the effects of sport expertise on mental rotation. PMID:29071008

Combining analytical hierarchy process and agglomerative hierarchical clustering in search of expert consensus in green corridors development management.

PubMed

Shapira, Aviad; Shoshany, Maxim; Nir-Goldenberg, Sigal

2013-07-01

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts-landscape architects, regional planners, and geographers-revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.

Selecting Health Care Improvement Projects: A Methodology Integrating Cause-and-Effect Diagram and Analytical Hierarchy Process.

PubMed

Testik, Özlem Müge; Shaygan, Amir; Dasdemir, Erdi; Soydan, Guray

It is often vital to identify, prioritize, and select quality improvement projects in a hospital. Yet, a methodology, which utilizes experts' opinions with different points of view, is needed for better decision making. The proposed methodology utilizes the cause-and-effect diagram to identify improvement projects and construct a project hierarchy for a problem. The right improvement projects are then prioritized and selected using a weighting scheme of analytical hierarchy process by aggregating experts' opinions. An approach for collecting data from experts and a graphical display for summarizing the obtained information are also provided. The methodology is implemented for improving a hospital appointment system. The top-ranked 2 major project categories for improvements were identified to be system- and accessibility-related causes (45%) and capacity-related causes (28%), respectively. For each of the major project category, subprojects were then ranked for selecting the improvement needs. The methodology is useful in cases where an aggregate decision based on experts' opinions is expected. Some suggestions for practical implementations are provided.

Clean birth kits to improve birth practices: development and testing of a country level decision support tool.

PubMed

Hundley, Vanora A; Avan, Bilal I; Ahmed, Haris; Graham, Wendy J

2012-12-19

Clean birth practices can prevent sepsis, one of the leading causes of both maternal and newborn mortality. Evidence suggests that clean birth kits (CBKs), as part of package that includes education, are associated with a reduction in newborn mortality, omphalitis, and puerperal sepsis. However, questions remain about how best to approach the introduction of CBKs in country. We set out to develop a practical decision support tool for programme managers of public health systems who are considering the potential role of CBKs in their strategy for care at birth. Development and testing of the decision support tool was a three-stage process involving an international expert group and country level testing. Stage 1, the development of the tool was undertaken by the Birth Kit Working Group and involved a review of the evidence, a consensus meeting, drafting of the proposed tool and expert review. In Stage 2 the tool was tested with users through interviews (9) and a focus group, with federal and provincial level decision makers in Pakistan. In Stage 3 the findings from the country level testing were reviewed by the expert group. The decision support tool comprised three separate algorithms to guide the policy maker or programme manager through the specific steps required in making the country level decision about whether to use CBKs. The algorithms were supported by a series of questions (that could be administered by interview, focus group or questionnaire) to help the decision maker identify the information needed. The country level testing revealed that the decision support tool was easy to follow and helpful in making decisions about the potential role of CBKs. Minor modifications were made and the final algorithms are presented. Testing of the tool with users in Pakistan suggests that the tool facilitates discussion and aids decision making. However, testing in other countries is needed to determine whether these results can be replicated and to identify how the tool can be adapted to meet country specific needs.

[Health Impact Assessment: opportunity for participative decision-making or persuasive tool for decisions already taken?].

PubMed

Sturloni, Giancarlo

2016-01-01

The Health Impact Assessment (HIA) has already been tested in dozens of nations, including Italy, and the reflection is now mature enough to allow a first evaluation of its effective capacity to offer an inclusive tool for prevention. The analysis focuses in particular on the HIA ability to address, through a participatory approach, one of its founding values: the democratic nature of decisions with an impact on public health. In most cases, the experiments carried out so far seem to be disappointing: the participation is often absent or performed in a rhetorical form. Sometimes the HIA has even been used in an instrumental way to justify decisions already taken, with the only result to further erode the credibility of experts and institutions. In this work, however, the author will try to show how, on the contrary, a greater involvement in the evaluation and decision-making processes could improve the effectiveness of HIA in terms of prevention, while at the same time promoting a relationship of trust between experts, institutions, and citizens on which to establish an ecologically and socially sustainable development.

Frontal cortex electrophysiology in reward- and punishment-related feedback processing during advice-guided decision making: An interleaved EEG-DC stimulation study.

PubMed

Wischnewski, Miles; Bekkering, Harold; Schutter, Dennis J L G

2018-04-01

During decision making, individuals are prone to rely on external cues such as expert advice when the outcome is not known. However, the electrophysiological correlates associated with outcome uncertainty and the use of expert advice are not completely understood. The feedback-related negativity (FRN), P3a, and P3b are event-related brain potentials (ERPs) linked to dissociable stages of feedback and attentional processing during decision making. Even though these ERPs are influenced by both reward- and punishment-related feedback, it remains unclear how extrinsic information during uncertainty modulates these brain potentials. In this study, the effects of advice cues on decision making were investigated in two separate experiments. In the first experiment, electroencephalography (EEG) was recorded in healthy volunteers during a decision-making task in which the participants received reward or punishment feedback preceded by novice, amateur, or expert advice. The results showed that the P3a component was significantly influenced by the subjective predictive value of an advice cue, whereas the FRN and P3b were unaffected by the advice cues. In the second, sham-controlled experiment, cathodal transcranial direct current stimulation (ctDCS) was administered in conjunction with EEG in order to explore the direct contributions of the frontal cortex to these brain potentials. Results showed no significant change in either advice-following behavior or decision times. However, ctDCS did decrease FRN amplitudes as compared to sham, with no effect on the P3a or P3b. Together, these findings suggest that advice information may act primarily on attention allocation during feedback processing, whereas the electrophysiological correlates of the detection and updating of internal prediction models are not affected.

Eyes on the prize: reflections on the impact of the evolving digital ecology on the librarian as expert intermediary and knowledge coach, 1969–2009*

PubMed Central

Homan, J. Michael

2010-01-01

Objective: The 2009 Janet Doe Lecture reflects on the continuing value and increasing return on investment of librarian-mediated services in the constantly evolving digital ecology and complex knowledge environment of the health sciences. Setting: The interrelationship of knowledge, decision making based on knowledge, technology used to access and retrieve knowledge, and the important linkage roles of expert librarian intermediaries is examined. Methodology: Professional experiences from 1969 to 2009, occurring during a time of unprecedented changes in the digital ecology of librarianship, are the base on which the evolving role and value of librarians as knowledge coaches and expert intermediaries are examined. Conclusion: Librarian-mediated services linking knowledge and critical decision making in health care have become more valuable than ever as technology continues to reshape an increasingly complex knowledge environment. PMID:20098655

A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses

PubMed Central

Zhang, Chao; Li, Deyu; Yan, Yan

2015-01-01

In medical science, disease diagnosis is one of the difficult tasks for medical experts who are confronted with challenges in dealing with a lot of uncertain medical information. And different medical experts might express their own thought about the medical knowledge base which slightly differs from other medical experts. Thus, to solve the problems of uncertain data analysis and group decision making in disease diagnoses, we propose a new rough set model called dual hesitant fuzzy multigranulation rough set over two universes by combining the dual hesitant fuzzy set and multigranulation rough set theories. In the framework of our study, both the definition and some basic properties of the proposed model are presented. Finally, we give a general approach which is applied to a decision making problem in disease diagnoses, and the effectiveness of the approach is demonstrated by a numerical example. PMID:26858772

The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.

PubMed

Băceanu, Adrian; Atasiei, Ionuţ; Chazard, Emmanuel; Leroy, Nicolas

2009-01-01

An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

Reforming Pentagon Decisionmaking

DTIC Science & Technology

2006-01-01

that people should make decisions as rationally as possible and that deviations from the rational ideal are undesirable. Recently, however...warfighting; therefore, a rational as opposed to an intuitive system makes sense for investment decisions . Third, many Pentagon planning problems... rational planning processes, consensus among experts is that people use both intuitive and rational techniques to make good decisions F E A T U R E

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review.

PubMed

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh; Sadiq, Rehan

2015-01-01

Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Decision Making in Action: Applying Research to Practice

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Hart, Sandra G. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment: Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Scenarios in Social-Ecological Systems: Co-Producing Futures in Arctic Alaska

NASA Astrophysics Data System (ADS)

Lovecraft, A. L.; Eicken, H.

2016-12-01

Companies use scenarios to gain the capacity to think ahead in rapidly changing complex competitive environments and make crucial decisions in absence of complete information about the future. Currently, at many regional scales of governance there is a growing need for tools that enable the actors at local-scales to address pressing concerns in the midst of uncertainty. This is particularly true of areas experiencing rapidly changing environments (e.g., drought, floods, diminishing sea ice, erosion) and complex social problems (e.g., remote communities, resource extraction, threatened cultures). Resilience theory and deliberative democracy both promote governance by informed actors in an effort to produce decisions that avoid social-environmental collapse. The former focusing on resilient ecosystems, the latter on informed social choices. Scenario exercises produce neither forecasts of what is to come nor are they visions of what participants would like to happen. Rather, they produce pertinent and accurate information related to questions of "what would happen if…" and thus provide the possibility of strategic decision-making to reduce risk and promote community resilience. Scenarios can be forms of social learning and among local-scale experts they create a deliberative process to make decisions about proactive adaptation. This talk represents the results from two projects from Alaska's Arctic Slope region. Resident expert participants from the Northwest Arctic and North Slope Boroughs addressed the focal question "What is needed for healthy sustainable communities by 2040?" Our findings reinforce the growing evidence from studies related to Arctic community sustainability and human development that indicate tight connections between fate-control, health, and environmental change. Our work differs, however, in using a future studies approach. The participants are addressing social-ecological resilience from a proactive standpoint thinking long-term about local and regional scale concerns rather than examining global-scale forecasts for near-term decision-making. The results contribute to a multi-disciplinary cross-cultural discussion of the importance of innovative thinking at the local scale and future directions for geophysical researchers in a rapidly changing Arctic.

Diagnostic instrumentation aboard ISS: just-in-time training for non-physician crewmembers.

PubMed

Foale, C Michael; Kaleri, Alexander Y; Sargsyan, Ashot E; Hamilton, Douglas R; Melton, Shannon; Martin, David; Dulchavsky, Scott A

2005-06-01

The performance of complex tasks on the International Space Station (ISS) requires significant preflight crew training commitments and frequent skill and knowledge refreshment. This report documents a recently developed "just-in-time" training methodology, which integrates preflight hardware familiarization and procedure training with an on-orbit CD-ROM-based skill enhancement. This "just-in-time" concept was used to support real-time remote expert guidance to complete ultrasound examinations using the ISS Human Research Facility (HRF). An American and Russian ISS crewmember received 2 h of "hands on" ultrasound training 8 mo prior to the on-orbit ultrasound exam. A CD-ROM-based Onboard Proficiency Enhancement (OPE) interactive multimedia program consisting of memory enhancing tutorials, and skill testing exercises, was completed by the crewmember 6 d prior to the on-orbit ultrasound exam. The crewmember was then remotely guided through a thoracic, vascular, and echocardiographic examination by ultrasound imaging experts. Results of the CD-ROM-based OPE session were used to modify the instructions during a complete 35-min real-time thoracic, cardiac, and carotid/jugular ultrasound study. Following commands from the ground-based expert, the crewmember acquired all target views and images without difficulty. The anatomical content and fidelity of ultrasound video were adequate for clinical decision making. Complex ultrasound experiments with expert guidance were performed with high accuracy following limited preflight training and multimedia based in-flight review, despite a 2-s communication latency. In-flight application of multimedia proficiency enhancement software, coupled with real-time remote expert guidance, facilitates the successful performance of ultrasound examinations on orbit and may have additional terrestrial and space applications.

Diagnostic instrumentation aboard ISS: just-in-time training for non-physician crewmembers

NASA Technical Reports Server (NTRS)

Foale, C. Michael; Kaleri, Alexander Y.; Sargsyan, Ashot E.; Hamilton, Douglas R.; Melton, Shannon; Martin, David; Dulchavsky, Scott A.

2005-01-01

INTRODUCTION: The performance of complex tasks on the International Space Station (ISS) requires significant preflight crew training commitments and frequent skill and knowledge refreshment. This report documents a recently developed "just-in-time" training methodology, which integrates preflight hardware familiarization and procedure training with an on-orbit CD-ROM-based skill enhancement. This "just-in-time" concept was used to support real-time remote expert guidance to complete ultrasound examinations using the ISS Human Research Facility (HRF). METHODS: An American and Russian ISS crewmember received 2 h of "hands on" ultrasound training 8 mo prior to the on-orbit ultrasound exam. A CD-ROM-based Onboard Proficiency Enhancement (OPE) interactive multimedia program consisting of memory enhancing tutorials, and skill testing exercises, was completed by the crewmember 6 d prior to the on-orbit ultrasound exam. The crewmember was then remotely guided through a thoracic, vascular, and echocardiographic examination by ultrasound imaging experts. RESULTS: Results of the CD-ROM-based OPE session were used to modify the instructions during a complete 35-min real-time thoracic, cardiac, and carotid/jugular ultrasound study. Following commands from the ground-based expert, the crewmember acquired all target views and images without difficulty. The anatomical content and fidelity of ultrasound video were adequate for clinical decision making. CONCLUSIONS: Complex ultrasound experiments with expert guidance were performed with high accuracy following limited preflight training and multimedia based in-flight review, despite a 2-s communication latency. In-flight application of multimedia proficiency enhancement software, coupled with real-time remote expert guidance, facilitates the successful performance of ultrasound examinations on orbit and may have additional terrestrial and space applications.

Multidimensional model to assess the readiness of Saudi Arabia to implement evidence based child maltreatment prevention programs at a large scale.

PubMed

Almuneef, Maha A; Qayad, Mohamed; Noor, Ismail K; Al-Eissa, Majid A; Albuhairan, Fadia S; Inam, Sarah; Mikton, Christopher

2014-03-01

There has been increased awareness of child maltreatment in Saudi Arabia recently. This study assessed the readiness for implementing large-scale evidence-based child maltreatment prevention programs in Saudi Arabia. Key informants, who were key decision makers and senior managers in the field of child maltreatment, were invited to participate in the study. A multidimensional tool, developed by WHO and collaborators from several middle and low income countries, was used to assess 10 dimensions of readiness. A group of experts also gave an objective assessment of the 10 dimensions and key informants' and experts' scores were compared. On a scale of 100, the key informants gave a readiness score of 43% for Saudi Arabia to implement large-scale, evidence-based CM prevention programs, and experts gave an overall readiness score of 40%. Both the key informants and experts agreed that 4 of the dimensions (attitudes toward child maltreatment prevention, institutional links and resources, material resources, and human and technical resources) had low readiness scores (<5) each and three dimensions (knowledge of child maltreatment prevention, scientific data on child maltreatment prevention, and will to address child maltreatment problem) had high readiness scores (≥5) each. There was significant disagreement between key informants and experts on the remaining 3 dimensions. Overall, Saudi Arabia has a moderate/fair readiness to implement large-scale child maltreatment prevention programs. Capacity building; strengthening of material resources; and improving institutional links, collaborations, and attitudes toward the child maltreatment problem are required to improve the country's readiness to implement such programs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Knowledge translation from continuing education to physiotherapy practice in classifying patients with low back pain.

PubMed

Karvonen, Eira; Paatelma, Markku; Kesonen, Jukka-Pekka; Heinonen, Ari O

2015-05-01

Physical therapists have used continuing education as a method of improving their skills in conducting clinical examination of patients with low back pain (LBP). The purpose of this study was to evaluate how well the pathoanatomical classification of patients in acute or subacute LBP can be learned and applied through a continuing education format. The patients were seen in a direct access setting. The study was carried out in a large health-care center in Finland. The analysis included a total of 57 patient evaluations generated by six physical therapists on patients with LBP. We analyzed the consistency and level of agreement of the six physiotherapists' (PTs) diagnostic decisions, who participated in a 5-day, intensive continuing education session and also compared those with the diagnostic opinions of two expert physical therapists, who were blind to the original diagnostic decisions. Evaluation of the physical therapists' clinical examination of the patients was conducted by the two experts, in order to determine the accuracy and percentage agreement of the pathoanatomical diagnoses. The percentage of agreement between the experts and PTs was 72-77%. The overall inter-examiner reliability (kappa coefficient) for the subgroup classification between the six PTs and two experts was 0.63 [95% confidence interval (CI): 0.47-0.77], indicating good agreement between the PTs and the two experts. The overall inter-examiner reliability between the two experts was 0.63 (0.49-0.77) indicating good level of agreement. Our results indicate that PTs' were able to apply their continuing education training to clinical reasoning and make consistently accurate pathoanatomic based diagnostic decisions for patients with LBP. This would suggest that continuing education short-courses provide a reasonable format for knowledge translation (KT) by which physical therapists can learn and apply new information related to the examination and differential diagnosis of patients in acute or subacute LBP.

Understanding information synthesis in oral surgery for the design of systems for clinical information technology.

PubMed

Suebnukarn, Siriwan; Chanakarn, Piyawadee; Phisutphatthana, Sirada; Pongpatarat, Kanchala; Wongwaithongdee, Udom; Oupadissakoon, Chanekrid

2015-12-01

An understanding of the processes of clinical decision-making is essential for the development of health information technology. In this study we have analysed the acquisition of information during decision-making in oral surgery, and analysed cognitive tasks using a "think-aloud" protocol. We studied the techniques of processing information that were used by novices and experts as they completed 4 oral surgical cases modelled from data obtained from electronic hospital records. We studied 2 phases of an oral surgeon's preoperative practice including the "diagnosis and planning of treatment" and "preparing for a procedure". A framework analysis approach was used to analyse the qualitative data, and a descriptive statistical analysis was made of the quantitative data. The results showed that novice surgeons used hypotheticodeductive reasoning, whereas experts recognised patterns to diagnose and manage patients. Novices provided less detail when they prepared for a procedure. Concepts regarding "signs", "importance", "decisions", and "process" occurred most often during acquisition of information by both novices and experts. Based on these results, we formulated recommendations for the design of clinical information technology that would help to improve the acquisition of clinical information required by oral surgeons at all levels of expertise in their clinical decision-making. Copyright © 2015 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Using a situation awareness approach to determine decision-making behaviour in squash.

PubMed

Murray, Stafford; James, Nic; Perš, Janez; Mandeljc, Rok; Vučković, Goran

2018-06-01

Situation awareness (SA) refers to the awareness of all relevant sources of information, an ability to synthesise this information using domain knowledge gained from past experiences and the ability to physically respond to a situation. Expert-novice differences have been widely reported in decision-making in complex situations although determining the small differences in expert behaviour are more elusive. This study considered how expert squash players use SA to decide on what shot to play. Matches at the 2010 (n = 14) and 2011 (n = 27) Rowe British Grand Prix were recorded and processed using Tracker software. Shot type, ball location, players' positions on court and movement parameters between the time an opponent played a shot prior to the player's shot to the time of the opponent's following shot were captured 25 times per second. Six SA clusters were named to relate to the outcome of a shot ranging from a defensive shot played under pressure to create time to an attempted winner played under no pressure with the opponent out of position. This new methodology found fine-grained SA differences in expert behaviour, even for the same shot type played from the same court area, beyond the usual expert-novice differences.

Integrating local, expert, and practical knowledge in community remediation and revitalization

EPA Science Inventory

Researchers and natural resource managers often develop tools and methods to facilitate the inclusion of science in local environmental decision-making. The eternal hope is to find that model or concept that provides the “right” information to support these decisions....

Decision Support System for Disability Assessment and Intervention.

ERIC Educational Resources Information Center

Dowler, Denetta L.; And Others

1991-01-01

Constructed decision support system to aid referral of good candidates for rehabilitation from Social Security Administration to rehabilitation counselors. Three layers of system were gross screening based on policy guidelines, training materials, and interviews with experts; physical and mental functional capacity items derived from policy…

The tale of hearts and reason: the influence of mood on decision making.

PubMed

Laborde, Sylvain; Raab, Markus

2013-08-01

In decision-making research, one important aspect of real-life decisions has so far been neglected: the mood of the decision maker when generating options. The authors tested the use of the take-the-first (TTF) heuristic and extended the TTF model to understand how mood influences the option-generation process of individuals in two studies, the first using a between-subjects design (30 nonexperts, 30 near-experts, and 30 experts) and the second conceptually replicating the first using a within-subject design (30 nonexperts). Participants took part in an experimental option-generation task, with 31 three-dimensional videos of choices in team handball. Three moods were elicited: positive, neutral, and negative. The findings (a) replicate previous results concerning TTF and (b) show that the option-generation process was associated with the physiological component of mood, supporting the neurovisceral integration model. The extension of TTF to processing emotional factors is an important step forward in explaining fast choices in real-life situations.

Thinking like an expert: surgical decision making as a cyclical process of being aware.

PubMed

Cristancho, Sayra M; Apramian, Tavis; Vanstone, Meredith; Lingard, Lorelei; Ott, Michael; Forbes, Thomas; Novick, Richard

2016-01-01

Education researchers are studying the practices of high-stake professionals as they learn how to better train for flexibility under uncertainty. This study explores the "Reconciliation Cycle" as the core element of an intraoperative decision-making model of how experienced surgeons assess and respond to challenges. We analyzed 32 semistructured interviews using constructivist grounded theory to develop a model of intraoperative decision making. Using constant comparison analysis, we built on this model with 9 follow-up interviews about the most challenging cases described in our dataset. The Reconciliation Cycle constituted an iterative process of "gaining" and "transforming information." The cyclical nature of surgeons' decision making suggested that transforming information requires a higher degree of awareness, not yet accounted by current conceptualizations of situation awareness. This study advances the notion of situation awareness in surgery. This characterization will support further investigations on how expert and nonexpert surgeons implement strategies to cope with unexpected events. Copyright © 2016 Elsevier Inc. All rights reserved.

The application of the heuristic-systematic processing model to treatment decision making about prostate cancer.

PubMed

Steginga, Suzanne K; Occhipinti, Stefano

2004-01-01

The study investigated the utility of the Heuristic-Systematic Processing Model as a framework for the investigation of patient decision making. A total of 111 men recently diagnosed with localized prostate cancer were assessed using Verbal Protocol Analysis and self-report measures. Study variables included men's use of nonsystematic and systematic information processing, desire for involvement in decision making, and the individual differences of health locus of control, tolerance of ambiguity, and decision-related uncertainty. Most men (68%) preferred that decision making be shared equally between them and their doctor. Men's use of the expert opinion heuristic was related to men's verbal reports of decisional uncertainty and having a positive orientation to their doctor and medical care; a desire for greater involvement in decision making was predicted by a high internal locus of health control. Trends were observed for systematic information processing to increase when the heuristic strategy used was negatively affect laden and when men were uncertain about the probabilities for cure and side effects. There was a trend for decreased systematic processing when the expert opinion heuristic was used. Findings were consistent with the Heuristic-Systematic Processing Model and suggest that this model has utility for future research in applied decision making about health.

Considerations in development of expert systems for real-time space applications

NASA Technical Reports Server (NTRS)

Murugesan, S.

1988-01-01

Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications.

Semi-automatic generation of medical tele-expert opinion for primary care physician.

PubMed

Biermann, E; Rihl, J; Schenker, M; Standl, E

2003-01-01

A computer-based system has been developed for the generation of medical expert opinions on the insulin-resistance syndrome, based on clinical data obtained from primary care physicians. An expert opinion for each patient was generated by using a decision tree for entering individual text modules and by adding optional free text. The expert opinions were returned by e-mail, telefax or by ordinary mail. 1389 primary care physician sent anonymous data sets and requested expert opinions for a total of 3768 patients. Through the set up of a rule-based system an automation of the generation of the expert opinions could be achieved and the generation time dropped from initially 40 minutes to less than 5 minutes at the end. By using predefined text modules and a rule based system, a large number of medical expert opinions can be generated with relatively few additional resources.

Artificial intelligence within the chemical laboratory.

PubMed

Winkel, P

1994-01-01

Various techniques within the area of artificial intelligence such as expert systems and neural networks may play a role during the problem-solving processes within the clinical biochemical laboratory. Neural network analysis provides a non-algorithmic approach to information processing, which results in the ability of the computer to form associations and to recognize patterns or classes among data. It belongs to the machine learning techniques which also include probabilistic techniques such as discriminant function analysis and logistic regression and information theoretical techniques. These techniques may be used to extract knowledge from example patients to optimize decision limits and identify clinically important laboratory quantities. An expert system may be defined as a computer program that can give advice in a well-defined area of expertise and is able to explain its reasoning. Declarative knowledge consists of statements about logical or empirical relationships between things. Expert systems typically separate declarative knowledge residing in a knowledge base from the inference engine: an algorithm that dynamically directs and controls the system when it searches its knowledge base. A tool is an expert system without a knowledge base. The developer of an expert system uses a tool by entering knowledge into the system. Many, if not the majority of problems encountered at the laboratory level are procedural. A problem is procedural if it is possible to write up a step-by-step description of the expert's work or if it can be represented by a decision tree. To solve problems of this type only small expert system tools and/or conventional programming are required.(ABSTRACT TRUNCATED AT 250 WORDS)

Visualization of decision processes using a cognitive architecture

NASA Astrophysics Data System (ADS)

Livingston, Mark A.; Murugesan, Arthi; Brock, Derek; Frost, Wende K.; Perzanowski, Dennis

2013-01-01

Cognitive architectures are computational theories of reasoning the human mind engages in as it processes facts and experiences. A cognitive architecture uses declarative and procedural knowledge to represent mental constructs that are involved in decision making. Employing a model of behavioral and perceptual constraints derived from a set of one or more scenarios, the architecture reasons about the most likely consequence(s) of a sequence of events. Reasoning of any complexity and depth involving computational processes, however, is often opaque and challenging to comprehend. Arguably, for decision makers who may need to evaluate or question the results of autonomous reasoning, it would be useful to be able to inspect the steps involved in an interactive, graphical format. When a chain of evidence and constraint-based decision points can be visualized, it becomes easier to explore both how and why a scenario of interest will likely unfold in a particular way. In initial work on a scheme for visualizing cognitively-based decision processes, we focus on generating graphical representations of models run in the Polyscheme cognitive architecture. Our visualization algorithm operates on a modified version of Polyscheme's output, which is accomplished by augmenting models with a simple set of tags. We provide example visualizations and discuss properties of our technique that pose challenges for our representation goals. We conclude with a summary of feedback solicited from domain experts and practitioners in the field of cognitive modeling.

A data mining system for providing analytical information on brain tumors to public health decision makers.

PubMed

Santos, R S; Malheiros, S M F; Cavalheiro, S; de Oliveira, J M Parente

2013-03-01

Cancer is the leading cause of death in economically developed countries and the second leading cause of death in developing countries. Malignant brain neoplasms are among the most devastating and incurable forms of cancer, and their treatment may be excessively complex and costly. Public health decision makers require significant amounts of analytical information to manage public treatment programs for these patients. Data mining, a technology that is used to produce analytically useful information, has been employed successfully with medical data. However, the large-scale adoption of this technique has been limited thus far because it is difficult to use, especially for non-expert users. One way to facilitate data mining by non-expert users is to automate the process. Our aim is to present an automated data mining system that allows public health decision makers to access analytical information regarding brain tumors. The emphasis in this study is the use of ontology in an automated data mining process. The non-experts who tried the system obtained useful information about the treatment of brain tumors. These results suggest that future work should be conducted in this area. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Network approaches for expert decisions in sports.

PubMed

Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

2012-04-01

This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

Hospital-based expert model for health technology procurement planning in hospitals.

PubMed

Miniati, R; Cecconi, G; Frosini, F; Dori, F; Regolini, J; Iadanza, E; Biffi Gentili, G

2014-01-01

Although in the last years technology innovation in healthcare brought big improvements in care level and patient quality of life, hospital complexity and management cost became higher. For this reason, necessity of planning for medical equipment procurement within hospitals is getting more and more important in order to sustainable provide appropriate technology for both routine activity and innovative procedures. In order to support hospital decision makers for technology procurement planning, an expert model was designed as reported in the following paper. It combines the most widely used approaches for technology evaluation by taking into consideration Health Technology Assessment (HTA) and Medical Equipment Replacement Model (MERM). The designing phases include a first definition of prioritization algorithms, then the weighting process through experts' interviews and a final step for the model validation that included both statistical testing and comparison with real decisions. In conclusion, the designed model was able to provide a semi-automated tool that through the use of multidisciplinary information is able to prioritize different requests of technology acquisition in hospitals. Validation outcomes improved the model accuracy and created different "user profiles" according to the specific needs of decision makers.

Emerging Technologies for Environmental Remediation: Integrating Data and Judgment.

PubMed

Bates, Matthew E; Grieger, Khara D; Trump, Benjamin D; Keisler, Jeffrey M; Plourde, Kenton J; Linkov, Igor

2016-01-05

Emerging technologies present significant challenges to researchers, decision-makers, industry professionals, and other stakeholder groups due to the lack of quantitative risk, benefit, and cost data associated with their use. Multi-criteria decision analysis (MCDA) can support early decisions for emerging technologies when data is too sparse or uncertain for traditional risk assessment. It does this by integrating expert judgment with available quantitative and qualitative inputs across multiple criteria to provide relative technology scores. Here, an MCDA framework provides preliminary insights on the suitability of emerging technologies for environmental remediation by comparing nanotechnology and synthetic biology to conventional remediation methods. Subject matter experts provided judgments regarding the importance of criteria used in the evaluations and scored the technologies with respect to those criteria. The results indicate that synthetic biology may be preferred over nanotechnology and conventional methods for high expected benefits and low deployment costs but that conventional technology may be preferred over emerging technologies for reduced risks and development costs. In the absence of field data regarding the risks, benefits, and costs of emerging technologies, structuring evidence-based expert judgment through a weighted hierarchy of topical questions may be helpful to inform preliminary risk governance and guide emerging technology development and policy.

A demonstration of expert systems applications in transportation engineering : volume I, transportation engineers and expert systems.

DOT National Transportation Integrated Search

1987-01-01

Expert systems, a branch of artificial-intelligence studies, is introduced with a view to its relevance in transportation engineering. Knowledge engineering, the process of building expert systems or transferring knowledge from human experts to compu...

Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities.

PubMed

Ramanujan, Devarajan; Bernstein, William Z; Chandrasegaran, Senthil K; Ramani, Karthik

2017-01-01

The rapid rise in technologies for data collection has created an unmatched opportunity to advance the use of data-rich tools for lifecycle decision-making. However, the usefulness of these technologies is limited by the ability to translate lifecycle data into actionable insights for human decision-makers. This is especially true in the case of sustainable lifecycle design (SLD), as the assessment of environmental impacts, and the feasibility of making corresponding design changes, often relies on human expertise and intuition. Supporting human sense-making in SLD requires the use of both data-driven and user-driven methods while exploring lifecycle data. A promising approach for combining the two is through the use of visual analytics (VA) tools. Such tools can leverage the ability of computer-based tools to gather, process, and summarize data along with the ability of human-experts to guide analyses through domain knowledge or data-driven insight. In this paper, we review previous research that has created VA tools in SLD. We also highlight existing challenges and future opportunities for such tools in different lifecycle stages-design, manufacturing, distribution & supply chain, use-phase, end-of-life, as well as life cycle assessment. Our review shows that while the number of VA tools in SLD is relatively small, researchers are increasingly focusing on the subject matter. Our review also suggests that VA tools can address existing challenges in SLD and that significant future opportunities exist.

Consideration of Insulin Pumps or Continuous Glucose Monitors by Adolescents With Type 1 Diabetes and Their Parents: Stakeholder Engagement in the Design of Web-Based Decision Aids.

PubMed

Wysocki, Tim; Hirschfeld, Fiona; Miller, Louis; Izenberg, Neil; Dowshen, Steven A; Taylor, Alex; Milkes, Amy; Shinseki, Michelle T; Bejarano, Carolina; Kozikowski, Chelsea; Kowal, Karen; Starr-Ashton, Penny; Ross, Judith L; Kummer, Mark; Carakushansky, Mauri; Lyness, D'Arcy; Brinkman, William; Pierce, Jessica; Fiks, Alexander; Christofferson, Jennifer; Rafalko, Jessica; Lawson, Margaret L

2016-08-01

This article describes the stakeholder-driven design, development, and testing of web-based, multimedia decision aids for youth with type 1 diabetes who are considering the insulin pump or continuous glucose monitoring and their parents. This is the initial phase of work designed to develop and evaluate the efficacy of these decision aids in promoting improved decision-making engagement with use of a selected device. Qualitative interviews of 36 parents and adolescents who had previously faced these decisions and 12 health care providers defined the content, format and structure of the decision aids. Experts in children's health media helped the research team to plan, create, and refine multimedia content and its presentation. A web development firm helped organize the content into a user-friendly interface and enabled tracking of decision aid utilization. Throughout, members of the research team, adolescents, parents, and 3 expert consultants offered perspectives about the website content, structure, and function until the design was complete. With the decision aid websites completed, the next phase of the project is a randomized controlled trial of usual clinical practice alone or augmented by use of the decision aid websites. Stakeholder-driven development of multimedia, web-based decision aids requires meticulous attention to detail but can yield exceptional resources for adolescents and parents contemplating major changes to their diabetes regimens. © 2016 The Author(s).

Rare cancers in children - The EXPeRT Initiative: a report from the European Cooperative Study Group on Pediatric Rare Tumors.

PubMed

Bisogno, G; Ferrari, A; Bien, E; Brecht, I B; Brennan, B; Cecchetto, G; Godzinski, J; Orbach, D; Reguerre, Y; Stachowicz-Stencel, T; Schneider, D T

2012-10-01

The low incidence and the heterogeneity of very rare tumors (VRTs) demand for international cooperation. In 2008, EXPeRT (European Cooperative Study Group for Pediatric Rare Tumors) was founded by national groups from Italy, France, United Kingdom, Poland and Germany. The first aims of EXPeRT were to agree on a uniform definition of VRTs and to develop the currently most relevant scientific questions. Current initiatives include international data exchange, retrospective and prospective studies of specific entities, and the development of harmonized and internationally recognized guidelines. Moreover, EXPeRT established a network for expert consultation to assist in clinical decision in VRTs. © Georg Thieme Verlag KG Stuttgart · New York.

SigmaCLIPSE = presentation management + NASA CLI PS + SQL

NASA Technical Reports Server (NTRS)

Weiss, Bernard P., Jr.

1990-01-01

SigmaCLIPSE provides an expert systems and 'intelligent' data base development program for diverse systems integration environments that require support for automated reasoning and expert systems technology, presentation management, and access to 'intelligent' SQL data bases. The SigmaCLIPSE technology and and its integrated ability to access 4th generation application development and decision support tools through a portable SQL interface, comprises a sophisticated software development environment for solving knowledge engineering and expert systems development problems in information intensive commercial environments -- financial services, health care, and distributed process control -- where the expert system must be extendable -- a major architectural advantage of NASA CLIPS. SigmaCLIPSE is a research effort intended to test the viability of merging SQL data bases with expert systems technology.

Deepening the quality of clinical reasoning and decision-making in rural hospital nursing practice.

PubMed

Sedgwick, M G; Grigg, L; Dersch, S

2014-01-01

Rural acute care nursing requires an extensive breadth and depth of knowledge as well as the ability to quickly reason through problems in order to make sound clinical decisions. This reasoning often occurs within an environment that has minimal medical or ancillary support. Registered nurses (RN) new to rural nursing, and employers, have raised concerns about patient safety while new nurses make the transition into rural practice. In addition, feeling unprepared for the rigors of rural hospital nursing practice is a central issue influencing RN recruitment and retention. Understanding how rural RNs reason is a key element for identifying professional development needs and may support recruitment and retention of skilled rural nurses. The purpose of this study was to explore how rural RNs reason through clinical problems as well as to assess the quality of such reasoning. This study used a non-traditional approach for data collection. Fifteen rural acute care nurses with varying years of experience working in southern Alberta, Canada, were observed while they provided care to patients of varying acuity within a simulated rural setting. Following the simulation, semi-structured interviews were conducted using a substantive approach to critical thinking. Findings revealed that the ability to engage in deep clinical reasoning varied considerably among participants despite being given the same information under the same circumstances. Furthermore, the number of years of experience did not seem to be directly linked to the ability to engage in sound clinical reasoning. Novice nurses, however, did rely heavily on others in their decision making in order to ensure they were making the right decision. Hence, their relationships with other staff members influenced their ability to engage in clinical reasoning and decision making. In situations where the patient's condition was deteriorating quickly, regardless of years of experience, all of the participants depended on their colleagues when making decisions and reasoning throughout the simulation. Deep clinical reasoning and decision making is a function of reflection and self-correction that requires a critical self-awareness and is more about how nurses think than what they think. The degree of sophistication in reasoning of experts and novices is at times equivalent in that the reasoning of experts and novices can be somewhat limited and focused primarily on human physicality and less on conceptual knowledge. To become proficient in clinical reasoning, practice is necessary. The study supports the accumulating evidence that using clinical simulation and reflective interviewing that emphasize how clinical decisions are made enhances reasoning skills and confidence.

Development of a robust space power system decision model

NASA Astrophysics Data System (ADS)

Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert

2001-02-01

NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .

Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems

USGS Publications Warehouse

Neckles, Hilary A.; Lyons, James E.; Guntenspergen, Glenn R.; Shriver, W. Gregory; Adamowicz, Susan C.

2015-01-01

Most salt marshes in the USA have been degraded by human activities, and coastal managers are faced with complex choices among possible actions to restore or enhance ecosystem integrity. We applied structured decision making (SDM) to guide selection of monitoring variables and management priorities for salt marshes within the National Wildlife Refuge System in the northeastern USA. In general, SDM is a systematic process for decomposing a decision into its essential elements. We first engaged stakeholders in clarifying regional salt marsh decision problems, defining objectives and attributes to evaluate whether objectives are achieved, and developing a pool of alternative management actions for achieving objectives. Through this process, we identified salt marsh attributes that were applicable to monitoring National Wildlife Refuges on a regional scale and that targeted management needs. We then analyzed management decisions within three salt marsh units at Prime Hook National Wildlife Refuge, coastal Delaware, as a case example of prioritizing management alternatives. Values for salt marsh attributes were estimated from 2 years of baseline monitoring data and expert opinion. We used linear value modeling to aggregate multiple attributes into a single performance score for each alternative, constrained optimization to identify alternatives that maximized total management benefits subject to refuge-wide cost constraints, and used graphical analysis to identify the optimal set of alternatives for the refuge. SDM offers an efficient, transparent approach for integrating monitoring into management practice and improving the quality of management decisions.

Cognitive Task Analysis for Instruction in Single-Injection Ultrasound Guided-Regional Anesthesia

ERIC Educational Resources Information Center

Gucev, Gligor V.

2012-01-01

Cognitive task analysis (CTA) is methodology for eliciting knowledge from subject matter experts. CTA has been used to capture the cognitive processes, decision-making, and judgments that underlie expert behaviors. A review of the literature revealed that CTA has not yet been used to capture the knowledge required to perform ultrasound guided…

Hierarchical Thinking: A Cognitive Tool for Guiding Coherent Decision Making in Design Problem Solving

ERIC Educational Resources Information Center

Haupt, Grietjie

2018-01-01

This paper builds on two concepts, the first of which is the extended information processing model of expert design cognition. This proposes twelve internal psychological characteristics interacting with the external world of expert designers during the early phases of the design process. Here, I explore one of the characteristics, hierarchical…

Knowledge discovery from data as a framework to decision support in medical domains

PubMed Central

Gibert, Karina

2009-01-01

Introduction Knowledge discovery from data (KDD) is a multidisciplinary discipline which appeared in 1996 for “non trivial identifying of valid, novel, potentially useful, ultimately understandable patterns in data”. Pre-treatment of data and post-processing is as important as the data exploitation (Data Mining) itself. Different analysis techniques can be properly combined to produce explicit knowledge from data. Methods Hybrid KDD methodologies combining Artificial Intelligence with Statistics and visualization have been used to identify patterns in complex medical phenomena: experts provide prior knowledge (pK); it biases the search of distinguishable groups of homogeneous objects; support-interpretation tools (CPG) assisted experts in conceptualization and labelling of discovered patterns, consistently with pK. Results Patterns of dependency in mental disabilities supported decision-making on legislation of the Spanish Dependency Law in Catalonia. Relationships between type of neurorehabilitation treatment and patterns of response for brain damage are assessed. Patterns of the perceived QOL along time are used in spinal cord lesion to improve social inclusion. Conclusion Reality is more and more complex and classical data analyses are not powerful enough to model it. New methodologies are required including multidisciplinarity and stressing on production of understandable models. Interaction with the experts is critical to generate meaningful results which can really support decision-making, particularly convenient transferring the pK to the system, as well as interpreting results in close interaction with experts. KDD is a valuable paradigm, particularly when facing very complex domains, not well understood yet, like many medical phenomena.

In the public interest: assessing expert and stakeholder influence in public deliberation about biobanks.

PubMed

MacLean, Samantha; Burgess, Michael M

2010-07-01

Providing technical and experiential information without overwhelming participants' perspectives presents a major challenge to public involvement in policy decisions. This article reports the design and analysis of a case study on incorporating expert and stakeholder knowledge without including them as deliberators, while supporting deliberative participants' ability to introduce and critically assess different perspectives. Analysis of audio-recorded deliberations illustrates how expert and stakeholder knowledge was cited, criticized and incorporated into deliberations. In conclusion, separating experts and stakeholders from deliberations may be an important prima facie principle when the goal is to enhance citizen representation on technical issues and related policy.

Communications and tracking expert systems study

NASA Technical Reports Server (NTRS)

Leibfried, T. F.; Feagin, Terry; Overland, David

1987-01-01

The original objectives of the study consisted of five broad areas of investigation: criteria and issues for explanation of communication and tracking system anomaly detection, isolation, and recovery; data storage simplification issues for fault detection expert systems; data selection procedures for decision tree pruning and optimization to enhance the abstraction of pertinent information for clear explanation; criteria for establishing levels of explanation suited to needs; and analysis of expert system interaction and modularization. Progress was made in all areas, but to a lesser extent in the criteria for establishing levels of explanation suited to needs. Among the types of expert systems studied were those related to anomaly or fault detection, isolation, and recovery.

Expert decision-making strategies

NASA Technical Reports Server (NTRS)

Mosier, Kathleen L.

1991-01-01

A recognition-primed decisions (RPD) model is employed as a framework to investigate crew decision-making processes. The quality of information transfer, a critical component of the team RPD model and an indicator of the team's 'collective consciouness', is measured and analyzed with repect to crew performance. As indicated by the RPD model, timing and patterns of information search transfer were expected to reflect extensive and continual situation assessment, and serial evaluation of alternative states of the world or decision response options.

Combining Human and Machine Intelligence to Derive Agents' Behavioral Rules for Groundwater Irrigation

NASA Astrophysics Data System (ADS)

Hu, Y.; Quinn, C.; Cai, X.

2015-12-01

One major challenge of agent-based modeling is to derive agents' behavioral rules due to behavioral uncertainty and data scarcity. This study proposes a new approach to combine a data-driven modeling based on the directed information (i.e., machine intelligence) with expert domain knowledge (i.e., human intelligence) to derive the behavioral rules of agents considering behavioral uncertainty. A directed information graph algorithm is applied to identifying the causal relationships between agents' decisions (i.e., groundwater irrigation depth) and time-series of environmental, socio-economical and institutional factors. A case study is conducted for the High Plains aquifer hydrological observatory (HO) area, U.S. Preliminary results show that four factors, corn price (CP), underlying groundwater level (GWL), monthly mean temperature (T) and precipitation (P) have causal influences on agents' decisions on groundwater irrigation depth (GWID) to various extents. Based on the similarity of the directed information graph for each agent, five clusters of graphs are further identified to represent all the agents' behaviors in the study area as shown in Figure 1. Using these five representative graphs, agents' monthly optimal groundwater pumping rates are derived through the probabilistic inference. Such data-driven relationships and probabilistic quantifications are then coupled with a physically-based groundwater model to investigate the interactions between agents' pumping behaviors and the underlying groundwater system in the context of coupled human and natural systems.

20 CFR 405.220 - Decision by the Federal reviewing official.

Code of Federal Regulations, 2011 CFR

2011-04-01

... PROCESS FOR ADJUDICATING INITIAL DISABILITY CLAIMS Review of Initial Determinations by a Federal Reviewing... his or her decision, the Federal reviewing official may consult with a medical, psychological, or... evidence, the Federal reviewing official will consult with a medical or psychological expert through the...

Understanding and Interpreting Career Decision-Making Difficulties

ERIC Educational Resources Information Center

Amir, Tamar; Gati, Itamar; Kleiman, Tali

2008-01-01

This research develops and tests a procedure for interpreting individuals' responses in multiscale career assessments, using the Career Decision-Making Difficulties Questionnaire (CDDQ). In Study 1, criteria for ascertaining the credibility of responses were developed, based on the judgments of 39 career-counseling experts. In Study 2, the…

Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change

USGS Publications Warehouse

Thorne, Karen M.; Mattsson, Brady J.; Takekawa, John Y.; Cummings, Jonathan; Crouse, Debby; Block, Giselle; Bloom, Valary; Gerhart, Matt; Goldbeck, Steve; Huning, Beth; Sloop, Christina; Stewart, Mendel; Taylor, Karen; Valoppi, Laura

2015-01-01

Decision makers that are responsible for stewardship of natural resources face many challenges, which are complicated by uncertainty about impacts from climate change, expanding human development, and intensifying land uses. A systematic process for evaluating the social and ecological risks, trade-offs, and cobenefits associated with future changes is critical to maximize resilience and conserve ecosystem services. This is particularly true in coastal areas where human populations and landscape conversion are increasing, and where intensifying storms and sea-level rise pose unprecedented threats to coastal ecosystems. We applied collaborative decision analysis with a diverse team of stakeholders who preserve, manage, or restore tidal marshes across the San Francisco Bay estuary, California, USA, as a case study. Specifically, we followed a structured decision-making approach, and we using expert judgment developed alternative management strategies to increase the capacity and adaptability to manage tidal marsh resilience while considering uncertainties through 2050. Because sea-level rise projections are relatively confident to 2050, we focused on uncertainties regarding intensity and frequency of storms and funding. Elicitation methods allowed us to make predictions in the absence of fully compatible models and to assess short- and long-term trade-offs. Specifically we addressed two questions. (1) Can collaborative decision analysis lead to consensus among a diverse set of decision makers responsible for environmental stewardship and faced with uncertainties about climate change, funding, and stakeholder values? (2) What is an optimal strategy for the conservation of tidal marshes, and what strategy is robust to the aforementioned uncertainties? We found that when taking this approach, consensus was reached among the stakeholders about the best management strategies to maintain tidal marsh integrity. A Bayesian decision network revealed that a strategy considering sea-level rise and storms explicitly in wetland restoration planning and designs was optimal, and it was robust to uncertainties about management effectiveness and budgets. We found that strategies that avoided explicitly accounting for future climate change had the lowest expected performance based on input from the team. Our decision-analytic framework is sufficiently general to offer an adaptable template, which can be modified for use in other areas that include a diverse and engaged stakeholder group.

Writing as decision-making

NASA Technical Reports Server (NTRS)

Souther, J. W.

1981-01-01

The need to teach informational writing as a decision-making process is discussed. Situational analysis, its relationship to decisions in writing, and the need for relevant assignments are considered. Teaching students to ask the right questions is covered. The need to teach writing responsiveness is described. Three steps to get started and four teaching techniques are described. The information needs of the 'expert' and the 'manager' are contrasted.

Algorithms in the First-Line Treatment of Metastatic Clear Cell Renal Cell Carcinoma--Analysis Using Diagnostic Nodes.

PubMed

Rothermundt, Christian; Bailey, Alexandra; Cerbone, Linda; Eisen, Tim; Escudier, Bernard; Gillessen, Silke; Grünwald, Viktor; Larkin, James; McDermott, David; Oldenburg, Jan; Porta, Camillo; Rini, Brian; Schmidinger, Manuela; Sternberg, Cora; Putora, Paul M

2015-09-01

With the advent of targeted therapies, many treatment options in the first-line setting of metastatic clear cell renal cell carcinoma (mccRCC) have emerged. Guidelines and randomized trial reports usually do not elucidate the decision criteria for the different treatment options. In order to extract the decision criteria for the optimal therapy for patients, we performed an analysis of treatment algorithms from experts in the field. Treatment algorithms for the treatment of mccRCC from experts of 11 institutions were obtained, and decision trees were deduced. Treatment options were identified and a list of unified decision criteria determined. The final decision trees were analyzed with a methodology based on diagnostic nodes, which allows for an automated cross-comparison of decision trees. The most common treatment recommendations were determined, and areas of discordance were identified. The analysis revealed heterogeneity in most clinical scenarios. The recommendations selected for first-line treatment of mccRCC included sunitinib, pazopanib, temsirolimus, interferon-α combined with bevacizumab, high-dose interleukin-2, sorafenib, axitinib, everolimus, and best supportive care. The criteria relevant for treatment decisions were performance status, Memorial Sloan Kettering Cancer Center risk group, only or mainly lung metastases, cardiac insufficiency, hepatic insufficiency, age, and "zugzwang" (composite of multiple, related criteria). In the present study, we used diagnostic nodes to compare treatment algorithms in the first-line treatment of mccRCC. The results illustrate the heterogeneity of the decision criteria and treatment strategies for mccRCC and how available data are interpreted and implemented differently among experts. The data provided in the present report should not be considered to serve as treatment recommendations for the management of treatment-naïve patients with multiple metastases from metastatic clear cell renal cell carcinoma outside a clinical trial; however, the data highlight the different treatment options and the criteria used to select them. The diversity in decision making and how results from phase III trials can be interpreted and implemented differently in daily practice are demonstrated. ©AlphaMed Press.

Best practice strategies to safeguard drug prescribing and drug administration: an anthology of expert views and opinions.

PubMed

Seidling, Hanna M; Stützle, Marion; Hoppe-Tichy, Torsten; Allenet, Benoît; Bedouch, Pierrick; Bonnabry, Pascal; Coleman, Jamie J; Fernandez-Llimos, Fernando; Lovis, Christian; Rei, Maria Jose; Störzinger, Dominic; Taylor, Lenka A; Pontefract, Sarah K; van den Bemt, Patricia M L A; van der Sijs, Heleen; Haefeli, Walter E

2016-04-01

While evidence on implementation of medication safety strategies is increasing, reasons for selecting and relinquishing distinct strategies and details on implementation are typically not shared in published literature. We aimed to collect and structure expert information resulting from implementing medication safety strategies to provide advice for decision-makers. Medication safety experts with clinical expertise from thirteen hospitals throughout twelve European and North American countries shared their experience in workshop meetings, on-site-visits and remote structured interviews. We performed an expert-based, in-depth assessment of implementation of best-practice strategies to improve drug prescribing and drug administration. Workflow, variability and recommended medication safety strategies in drug prescribing and drug administration processes. According to the experts, institutions chose strategies that targeted process steps known to be particularly error-prone in the respective setting. Often, the selection was channeled by local constraints such as the e-health equipment and critically modulated by national context factors. In our study, the experts favored electronic prescribing with clinical decision support and medication reconciliation as most promising interventions. They agreed that self-assessment and introduction of medication safety boards were crucial to satisfy the setting-specific differences and foster successful implementation. While general evidence for implementation of strategies to improve medication safety exists, successful selection and adaptation of a distinct strategy requires a thorough knowledge of the institute-specific constraints and an ongoing monitoring and adjustment of the implemented measures.

Analysis and Lessons Learned from an Online, Consultative Dialogue between Community Leaders and Climate Experts

NASA Astrophysics Data System (ADS)

Sylak-Glassman, E.; Clavin, C.

2016-12-01

Common approaches to climate resilience planning in the United States rely upon participatory planning approaches and dialogues between decision-makers, science translators, and subject matter experts. In an effort to explore alternative approaches support community climate resilience planning, a pilot of a public-private collaboration called the Resilience Dialogues was held in February and March of 2016. The Resilience Dialogues pilot was an online, asynchronous conversation between community leaders and climate experts, designed to help communities begin the process of climate resilience planning. In order to identify lessons learned from the pilot, we analyzed the discourse of the facilitated dialogues, administered surveys and conducted interviews with participants. Our analysis of the pilot suggests that participating community leaders found value in the consultative dialogue with climate experts, despite limited community-originated requests for climate information. Community leaders most often asked for advice regarding adaptation planning, including specific engineering guidance and advice on how to engage community members around the topic of resilience. Community leaders that had access to downscaled climate data asked experts about how to incorporate the data into their existing planning processes. The guidance sought by community leaders during the pilot shows a large range of hurdles that communities face in using climate information to inform their decision-making processes. Having a forum that connects community leaders with relevant experts and other community leaders who have familiarity with both climate impacts and municipal planning processes would likely help communities accelerate their resilience efforts.

A proposed approach for quantitative benefit-risk assessment in diagnostic radiology guideline development: the American College of Radiology Appropriateness Criteria Example.

PubMed

Agapova, Maria; Bresnahan, Brian B; Higashi, Mitchell; Kessler, Larry; Garrison, Louis P; Devine, Beth

2017-02-01

The American College of Radiology develops evidence-based practice guidelines to aid appropriate utilization of radiological procedures. Panel members use expert opinion to weight trade-offs and consensus methods to rate appropriateness of imaging tests. These ratings include an equivocal range, assigned when there is disagreement about a technology's appropriateness and the evidence base is weak or for special circumstances. It is not clear how expert consensus merges with the evidence base to arrive at an equivocal rating. Quantitative benefit-risk assessment (QBRA) methods may assist decision makers in this capacity. However, many methods exist and it is not clear which methods are best suited for this application. We perform a critical appraisal of QBRA methods and propose several steps that may aid in making transparent areas of weak evidence and barriers to consensus in guideline development. We identify QBRA methods with potential to facilitate decision making in guideline development and build a decision aid for selecting among these methods. This study identified 2 families of QBRA methods suited to guideline development when expert opinion is expected to contribute substantially to decision making. Key steps to deciding among QBRA methods involve identifying specific benefit-risk criteria and developing a state-of-evidence matrix. For equivocal ratings assigned for reasons other than disagreement or weak evidence base, QBRA may not be needed. In the presence of disagreement but the absence of a weak evidence base, multicriteria decision analysis approaches are recommended; and in the presence of weak evidence base and the absence of disagreement, incremental net health benefit alone or combined with multicriteria decision analysis is recommended. Our critical appraisal further extends investigation of the strengths and limitations of select QBRA methods in facilitating diagnostic radiology clinical guideline development. The process of using the decision aid exposes and makes transparent areas of weak evidence and barriers to consensus. © 2016 John Wiley & Sons, Ltd.

Advancing Risk Analysis for Nanoscale Materials: Report from an International Workshop on the Role of Alternative Testing Strategies for Advancement: Advancing Risk Analysis for Nanoscale Materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shatkin, J. A.; Ong, Kimberly J.; Beaudrie, Christian

The Society for Risk Analysis (SRA) has a history of bringing thought leadership to topics of emerging risk. In September 2014, the SRA Emerging Nanoscale Materials Specialty Group convened an international workshop to examine the use of alternative testing strategies (ATS) for manufactured nanomaterials (NM) from a risk analysis perspective. Experts in NM environmental health and safety, human health, ecotoxicology, regulatory compliance, risk analysis, and ATS evaluated and discussed the state of the science for in vitro and other alternatives to traditional toxicology testing for NM. Based on this review, experts recommended immediate and near-term actions that would advance ATSmore » use in NM risk assessment. Three focal areas-human health, ecological health, and exposure considerations-shaped deliberations about information needs, priorities, and the next steps required to increase confidence in and use of ATS in NM risk assessment. The deliberations revealed that ATS are now being used for screening, and that, in the near term, ATS could be developed for use in read-across or categorization decision making within certain regulatory frameworks. Participants recognized that leadership is required from within the scientific community to address basic challenges, including standardizing materials, protocols, techniques and reporting, and designing experiments relevant to real-world conditions, as well as coordination and sharing of large-scale collaborations and data. Experts agreed that it will be critical to include experimental parameters that can support the development of adverse outcome pathways. Numerous other insightful ideas for investment in ATS emerged throughout the discussions and are further highlighted in this article.« less

A game-based platform for crowd-sourcing biomedical image diagnosis and standardized remote training and education of diagnosticians

NASA Astrophysics Data System (ADS)

Feng, Steve; Woo, Minjae; Chandramouli, Krithika; Ozcan, Aydogan

2015-03-01

Over the past decade, crowd-sourcing complex image analysis tasks to a human crowd has emerged as an alternative to energy-inefficient and difficult-to-implement computational approaches. Following this trend, we have developed a mathematical framework for statistically combining human crowd-sourcing of biomedical image analysis and diagnosis through games. Using a web-based smart game (BioGames), we demonstrated this platform's effectiveness for telediagnosis of malaria from microscopic images of individual red blood cells (RBCs). After public release in early 2012 (http://biogames.ee.ucla.edu), more than 3000 gamers (experts and non-experts) used this BioGames platform to diagnose over 2800 distinct RBC images, marking them as positive (infected) or negative (non-infected). Furthermore, we asked expert diagnosticians to tag the same set of cells with labels of positive, negative, or questionable (insufficient information for a reliable diagnosis) and statistically combined their decisions to generate a gold standard malaria image library. Our framework utilized minimally trained gamers' diagnoses to generate a set of statistical labels with an accuracy that is within 98% of our gold standard image library, demonstrating the "wisdom of the crowd". Using the same image library, we have recently launched a web-based malaria training and educational game allowing diagnosticians to compare their performance with their peers. After diagnosing a set of ~500 cells per game, diagnosticians can compare their quantified scores against a leaderboard and view their misdiagnosed cells. Using this platform, we aim to expand our gold standard library with new RBC images and provide a quantified digital tool for measuring and improving diagnostician training globally.

Advancing Risk Analysis for Nanoscale Materials: Report from an International Workshop on the Role of Alternative Testing Strategies for Advancement.

PubMed

Shatkin, J A; Ong, Kimberly J; Beaudrie, Christian; Clippinger, Amy J; Hendren, Christine Ogilvie; Haber, Lynne T; Hill, Myriam; Holden, Patricia; Kennedy, Alan J; Kim, Baram; MacDonell, Margaret; Powers, Christina M; Sharma, Monita; Sheremeta, Lorraine; Stone, Vicki; Sultan, Yasir; Turley, Audrey; White, Ronald H

2016-08-01

The Society for Risk Analysis (SRA) has a history of bringing thought leadership to topics of emerging risk. In September 2014, the SRA Emerging Nanoscale Materials Specialty Group convened an international workshop to examine the use of alternative testing strategies (ATS) for manufactured nanomaterials (NM) from a risk analysis perspective. Experts in NM environmental health and safety, human health, ecotoxicology, regulatory compliance, risk analysis, and ATS evaluated and discussed the state of the science for in vitro and other alternatives to traditional toxicology testing for NM. Based on this review, experts recommended immediate and near-term actions that would advance ATS use in NM risk assessment. Three focal areas-human health, ecological health, and exposure considerations-shaped deliberations about information needs, priorities, and the next steps required to increase confidence in and use of ATS in NM risk assessment. The deliberations revealed that ATS are now being used for screening, and that, in the near term, ATS could be developed for use in read-across or categorization decision making within certain regulatory frameworks. Participants recognized that leadership is required from within the scientific community to address basic challenges, including standardizing materials, protocols, techniques and reporting, and designing experiments relevant to real-world conditions, as well as coordination and sharing of large-scale collaborations and data. Experts agreed that it will be critical to include experimental parameters that can support the development of adverse outcome pathways. Numerous other insightful ideas for investment in ATS emerged throughout the discussions and are further highlighted in this article. © 2016 Society for Risk Analysis.

Learning to change taxonomies

NASA Astrophysics Data System (ADS)

Eneva, Elena; Petrushin, Valery A.

2002-03-01

Taxonomies are valuable tools for structuring and representing our knowledge about the world. They are widely used in many domains, where information about species, products, customers, publications, etc. needs to be organized. In the absence of standards, many taxonomies of the same entities can co-exist. A problem arises when data categorized in a particular taxonomy needs to be used by a procedure (methodology or algorithm) that uses a different taxonomy. Usually, a labor-intensive manual approach is used to solve this problem. This paper describes a machine learning approach which aids domain experts in changing taxonomies. It allows learning relationships between two taxonomies and mapping the data from one taxonomy into another. The proposed approach uses decision trees and bootstrapping for learning mappings of instances from the source to the target taxonomies. A C4.5 decision tree classifier is trained on a small manually labeled training set and applied to a randomly selected sample from the unlabeled data. The classification results are analyzed and the misclassified items are corrected and all items are added to the training set. This procedure is iterated until unlabeled data is available or an acceptable error rate is reached. In the latter case the last classifier is used to label all the remaining data. We test our approach on a database of products obtained from as grocery store chain and find that it performs well, reaching 92.6% accuracy while requiring the human expert to explicitly label only 18% of the entire data.

Scanning Rocket Impact Area with an UAV: First Results

NASA Astrophysics Data System (ADS)

Santos, C. C. C.; Costa, D. A. L. M.; Junior, V. L. S.; Silva, B. R. F.; Leite, D. L.; Junor, C. E. B. S.; Liberator, B. A.; Nogueira, M. B.; Senna, M. D.; Santiago, G. S.; Dantas, J. B. D.; Alsina, P. J.; Albuquerque, G. L. A.

2015-09-01

This paper presents the first subsystems developed for an UAV used in safety procedures of sounding rockets campaigns. The aim of this UAV is to scan the rocket impact area in order to search for unexpected boats. To achieve this mission, designers developed an image recognition algorithm, two human-machine interfaces and two communication links, one to control the drone and the other for receiving telemetry data. In this paper, developers take all major engineering decisions in order to overcome the project constraints. A secondary goal of the project is to encourage young people to take part in Brazilian space program. For this reason, most of designers are undergraduate students under supervision of experts.

Emotional engagement with participatory simulations as a tool for learning and decision-support for coupled human-natural systems: Flood hazards and urban development

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; Corey, B.; Camp, J. V.; John, N. J.; Sengupta, P.

2015-12-01

The complex interactions between land use and natural hazards pose serious challenges in education, research, and public policy. Where complex nonlinear interactions produce unintuitive results, interactive computer simulations can be useful tools for education and decision support. Emotions play important roles in cognition and learning, especially where risks are concerned. Interactive simulations have the potential to harness emotional engagement to enhance learning and understanding of risks in coupled human-natural systems. We developed a participatory agent-based simulation of cities at risk of river flooding. Participants play the role of managers of neighboring cities along a flood-prone river and make choices about building flood walls to protect their inhabitants. Simulated agents participate in dynamic real estate markets in which demand for property, and thus values and decisions to build, respond to experience with flooding over time. By reducing high-frequency low-magnitude flooding, flood walls may stimulate development, thus increasing tax revenues but also increasing vulnerability to uncommon floods that overtop the walls. Flood waves are launched stochastically and propagate downstream. Flood walls that restrict overbank flow at one city can increase the amplitude of a flood wave at neighboring cities, both up and downstream. We conducted a pilot experiment with a group of three pre-service teachers. The subjects successfully learned key concepts of risk tradeoffs and unintended consequences that can accompany flood-control measures. We also observed strong emotional responses, including hope, fear, and sense of loss. This emotional engagement with a model of coupled human-natural systems was very different from previous experiments on participatory simulations of purely natural systems for physics pedagogy. We conducted a second session in which the participants were expert engineers. We will present the results of these experiments and the prospects for using such models for middle-school, high-school, and post-secondary environmental science pedagogy, for improving public understanding of flood risks, and as decision support tools for planners.

Dramatically Polarized Opinion on the Role of Brachytherapy Boost in Management of High-risk Prostate Cancer: A Survey of North American Genitourinary Expert Radiation Oncologists.

PubMed

McClelland, Shearwood; Sandler, Kiri A; Degnin, Catherine; Chen, Yiyi; Mitin, Timur

2018-06-01

Three randomized clinical trials have established brachytherapy (BT) boost in combination with external beam radiation therapy (EBRT) and androgen deprivation therapy (ADT) as superior to definitive EBRT and ADT alone in terms of biochemical control (but not overall survival) at the expense of increased toxicity in men with high-risk (HR) prostate cancer (PCa). The current view regarding these 2 treatment algorithms among North American genitourinary (GU) experts is not known. A survey was distributed to 88 practicing North American GU physicians serving on decision-making committees of cooperative group research organizations. Questions pertained to opinions regarding BT as monotherapy for low-risk PCa and BT boost for HR PCa. Responders were asked to self-identify as BT experts versus non-experts. Treatment recommendations were correlated with practice patterns using the Fisher exact test. Forty-two radiation oncologists completed the survey, of whom 23 (55%) recommend EBRT and ADT alone and 19 (45%) recommend addition of BT boost. Twenty-five participants (60%) identified themselves as BT experts. Nearly 90% of those recommending BT boost were BT experts versus approximately 10% of non-BT experts (P < .001). Responders who recommended BT monotherapy as first-choice treatment for low-risk PCa were more likely to recommend BT boost for HR PCa (P < .0001). There is a dramatic polarization in opinions regarding incorporation of BT boost into EBRT + ADT therapy for patients with HR PCa among North American GU radiation oncology experts, who serve on decision-making committees and influence the national treatment guidelines and future clinical trials. Those who identify themselves as BT experts are significantly more likely to recommend BT boost. These findings are likely to influence the national guidelines and implementation of BT boost in current and future North American PCa clinical studies. Copyright © 2018 Elsevier Inc. All rights reserved.

When Billionaires Become Educational Experts

ERIC Educational Resources Information Center

Kumashiro, Kevin K.

2012-01-01

For years, critics have pointed to the decreasing ability of health-care professionals to make decisions and provide services because of the demands of insurance companies and health-management organizations to sustain profits. Health-care decisions are increasingly being made by the wrong people and for the wrong reasons. So, too, with public…

New auto-segment method of cerebral hemorrhage

NASA Astrophysics Data System (ADS)

Wang, Weijiang; Shen, Tingzhi; Dang, Hua

2007-12-01

A novel method for Computerized tomography (CT) cerebral hemorrhage (CH) image automatic segmentation is presented in the paper, which uses expert system that models human knowledge about the CH automatic segmentation problem. The algorithm adopts a series of special steps and extracts some easy ignored CH features which can be found by statistic results of mass real CH images, such as region area, region CT number, region smoothness and some statistic CH region relationship. And a seven steps' extracting mechanism will ensure these CH features can be got correctly and efficiently. By using these CH features, a decision tree which models the human knowledge about the CH automatic segmentation problem has been built and it will ensure the rationality and accuracy of the algorithm. Finally some experiments has been taken to verify the correctness and reasonable of the automatic segmentation, and the good correct ratio and fast speed make it possible to be widely applied into practice.

Effective Team Support: From Modeling to Software Agents

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie; Sycara, Katia

2003-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and engineers and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in modeling infrastructure and task infrastructure. Work is continuing under a different contract to complete empirical data collection, cognitive modeling, and the building of software agents to support the teams task.

Effective Team Support: From Task and Cognitive Modeling to Software Agents for Time-Critical Complex Work Environments

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie E.; Sycara, Katia

2005-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in completing a system for empirical data collection, cognitive modeling, and the building of software agents to support a team's tasks, and in running experiments for the collection of baseline data.

What Does it Mean to be Genomically Literate? National Human Genome Research Institute Meeting Report

PubMed Central

Hurle, Belen; Citrin, Toby; Jenkins, Jean F.; Kaphingst, Kimberly A.; Lamb, Neil; Roseman, Jo Ellen; Bonham, Vence L.

2014-01-01

Genomic discoveries will increasingly advance the science of medicine. Limited genomic literacy may adversely impact the public’s understanding and use of the power of genetics and genomics in health care and public health. In November 2011, a meeting was held by the National Human Genome Research Institute to examine the challenge of achieving genomic literacy for the general public, from K-12 to adult education. The role of the media in disseminating scientific messages and in perpetuating, or reducing, misconceptions was also discussed. Workshop participants agreed that genomic literacy will only be achieved through active engagement between genomics experts and the varied constituencies that comprise the public. This report summarizes the background, content, and outcomes from this meeting, including recommendations for a research agenda to inform decisions about how to advance genomic literacy in our society. PMID:23448722

The application of embodied conversational agents for mentoring African American STEM doctoral students

NASA Astrophysics Data System (ADS)

Gosha, Kinnis

This dissertation presents the design, development and short-term evaluation of an embodied conversational agent designed to mentor human users. An embodied conversational agent (ECA) was created and programmed to mentor African American computer science majors on their decision to pursue graduate study in computing. Before constructing the ECA, previous research in the fields of embodied conversational agents, relational agents, mentorship, telementorship and successful mentoring programs and practices for African American graduate students were reviewed. A survey used to find areas of interest of the sample population. Experts were then interviewed to collect information on those areas of interest and a dialogue for the ECA was constructed based on the interview's transcripts. A between-group, mixed method experiment was conducted with 37 African American male undergraduate computer science majors where one group used the ECA mentor while the other group pursued mentoring advice from a human mentor. Results showed no significant difference between the ECA and human mentor when dealing with career mentoring functions. However, the human mentor was significantly better than the ECA mentor when addressing psychosocial mentoring functions.

Site Suitability Analysis for Beekeeping via Analythical Hyrearchy Process, Konya Example

NASA Astrophysics Data System (ADS)

Sarı, F.; Ceylan, D. A.

2017-11-01

Over the past decade, the importance of the beekeeping activities has been emphasized in the field of biodiversity, ecosystems, agriculture and human health. Thus, efficient management and deciding correct beekeeping activities seems essential to maintain and improve productivity and efficiency. Due to this importance, considering the economic contributions to the rural area, the need for suitability analysis concept has been revealed. At this point, Multi Criteria Decision Analysis (MCDA) and Geographical Information Systems (GIS) integration provides efficient solutions to the complex structure of decision- making process for beekeeping activities. In this study, site suitability analysis via Analytical Hierarchy Process (AHP) was carried out for Konya city in Turkey. Slope, elevation, aspect, distance to water resources, roads and settlements, precipitation and flora criteria are included to determine suitability. The requirements, expectations and limitations of beekeeping activities are specified with the participation of experts and stakeholders. The final suitability map were validated with existing 117 beekeeping locations and Turkish Statistical Institute 2016 beekeeping statistics for Konya province.

Interdisciplinary cognitive task analysis: a strategy to develop a comprehensive endoscopic retrograde cholangiopancreatography protocol for use in fellowship training.

PubMed

Canopy, Erin; Evans, Matt; Boehler, Margaret; Roberts, Nicole; Sanfey, Hilary; Mellinger, John

2015-10-01

Endoscopic retrograde cholangiopancreatography is a challenging procedure performed by surgeons and gastroenterologists. We employed cognitive task analysis to identify steps and decision points for this procedure. Standardized interviews were conducted with expert gastroenterologists (7) and surgeons (4) from 4 institutions. A procedural step and cognitive decision point protocol was created from audio-taped transcriptions and was refined by 5 additional surgeons. Conceptual elements, sequential actions, and decision points were iterated for 5 tasks: patient preparation, duodenal intubation, selective cannulation, imaging interpretation with related therapeutic intervention, and complication management. A total of 180 steps were identified. Gastroenterologists identified 34 steps not identified by surgeons, and surgeons identified 20 steps not identified by gastroenterologists. The findings suggest that for complex procedures performed by diverse practitioners, more experts may help delineate distinctive emphases differentiated by training background and type of practice. Copyright © 2015 Elsevier Inc. All rights reserved.

The use of non-economic criteria in pricing and reimbursement decisions in Central and Eastern Europe: issues, trends and recommendations.

PubMed

Kolasa, Katarzyna; Kalo, Zoltan; Zah, Vladimir

2016-08-01

According to some experts, there is still room for improvement with regard to the inclusion of ethical considerations in Health Technology Assessment (HTA). The pros and cons of the introduction of non-economic criteria in the HTA process in Central and Eastern Europe (CEE) are discussed. In comparison to Western Europe, financial considerations are even more important in CEE settings; however, it could also be said that attachment to equity and justice is part of CEE's heritage. Therefore, the trade-off between conflicting principles is evaluated. Expert commentary: To ensure the right balance between equity and efficiency in decision making, the current HTA framework has to be further augmented to allow all conflicting criteria to be addressed to a satisfactory degree. Following other examples, the applicability of multi criteria decision analysis technique to CEE settings should be further investigated.

Fuzzy Logic Engine

NASA Technical Reports Server (NTRS)

Howard, Ayanna

2005-01-01

The Fuzzy Logic Engine is a software package that enables users to embed fuzzy-logic modules into their application programs. Fuzzy logic is useful as a means of formulating human expert knowledge and translating it into software to solve problems. Fuzzy logic provides flexibility for modeling relationships between input and output information and is distinguished by its robustness with respect to noise and variations in system parameters. In addition, linguistic fuzzy sets and conditional statements allow systems to make decisions based on imprecise and incomplete information. The user of the Fuzzy Logic Engine need not be an expert in fuzzy logic: it suffices to have a basic understanding of how linguistic rules can be applied to the user's problem. The Fuzzy Logic Engine is divided into two modules: (1) a graphical-interface software tool for creating linguistic fuzzy sets and conditional statements and (2) a fuzzy-logic software library for embedding fuzzy processing capability into current application programs. The graphical- interface tool was developed using the Tcl/Tk programming language. The fuzzy-logic software library was written in the C programming language.

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

PubMed

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

"No Wonder Out-of-Field Teachers Struggle!": Unpacking the Thinking of Expert Teachers

ERIC Educational Resources Information Center

Beswick, Kim; Fraser, Sharon; Crowley, Suzanne

2016-01-01

In this paper, the authors describe the initial stage of developing a framework designed to support out-of-field, less experiences or isolated mathematics and science teachers to make decisions about the use of resources in their teaching. The process highlighted the complexity and extent of the knowledge on which expert teachers draw in making…

Dealing with Conflicting or Consistent Medical Information on the Web: When Expert Information Breeds Laypersons' Doubts about Experts

ERIC Educational Resources Information Center

Kienhues, Dorothe; Stadtler, Marc; Bromme, Rainer

2011-01-01

The present study investigated how dealing with conflicting versus consistent medical information on the Web impacts on topic-specific and medicine-related epistemic beliefs as well as aspects of health decision making. One hundred mostly female university students were randomly assigned to three groups. Two intervention groups searched the Web…

TARPS: A Prototype Expert System for Training and Administration of Reserves (TAR) Officer Placement

DTIC Science & Technology

1991-09-01

OFFICER AQD=DC4 OR OFFICERAQD=DB6 OR OFFICER AQD=DA7 OR OFFICER--AQD-DA2 THEN BILLET AQD= ECK RULE 61 IF OFFICER DESIGNATOR=1317 AND OFFICER AQD=DB4 OR...Decision Support and Expert Systems, Macmillan Publishing Company, 1990. 71 INITIAL DISTRIBUTION LIST 1. Defense Technical Information Center 2 Cameron

Dynamic array processing for computationally intensive expert systems in CLIPS

NASA Technical Reports Server (NTRS)

Athavale, N. N.; Ragade, R. K.; Fenske, T. E.; Cassaro, M. A.

1990-01-01

This paper puts forth an architecture for implementing a loop for advanced data structure of arrays in CLIPS. An attempt is made to use multi-field variables in such an architecture to process a set of data during the decision making cycle. Also, current limitations on the expert system shells are discussed in brief in this paper. The resulting architecture is designed to circumvent the current limitations set by the expert system shell and also by the operating environment. Such advanced data structures are needed for tightly coupling symbolic and numeric computation modules.

An Expert-System Engine With Operative Probabilities

NASA Technical Reports Server (NTRS)

Orlando, N. E.; Palmer, M. T.; Wallace, R. S.

1986-01-01

Program enables proof-of-concepts tests of expert systems under development. AESOP is rule-based inference engine for expert system, which makes decisions about particular situation given user-supplied hypotheses, rules, and answers to questions drawn from rules. If knowledge base containing hypotheses and rules governing environment is available to AESOP, almost any situation within that environment resolved by answering questions asked by AESOP. Questions answered with YES, NO, MAYBE, DON'T KNOW, DON'T CARE, or with probability factor ranging from 0 to 10. AESOP written in Franz LISP for interactive execution.

Early-career experts essential for planetary sustainability

USGS Publications Warehouse

Lim, Michelle; Lynch, Abigail J.; Fernández-Llamazares, Alvaro; Balint, Lenke; Basher, Zeenatul; Chan, Ivis; Jaureguiberry, Pedro; Mohamed, A.A.A.; Mwampamba, Tuyeni H.; Palomo, Ignacio; Pliscoff, Patricio; Salimov, R.A.; Samakov, Aibek; Selomane, Odirilwe; Shrestha, Uttam B.; Sidorovich, Anna A.

2017-01-01

Early-career experts can play a fundamental role in achieving planetary sustainability by bridging generational divides and developing novel solutions to complex problems. We argue that intergenerational partnerships and interdisciplinary collaboration among early-career experts will enable emerging sustainability leaders to contribute fully to a sustainable future. We review 16 international, interdisciplinary, and sustainability-focused early-career capacity building programs. We conclude that such programs are vital to developing sustainability leaders of the future and that decision-making for sustainability is likely to be best served by strong institutional cultures that promote intergenerational learning and involvement.

A strategy for human factors/ergonomics: developing the discipline and profession.

PubMed

Dul, Jan; Bruder, Ralph; Buckle, Peter; Carayon, Pascale; Falzon, Pierre; Marras, William S; Wilson, John R; van der Doelen, Bas

2012-01-01

Human factors/ergonomics (HFE) has great potential to contribute to the design of all kinds of systems with people (work systems, product/service systems), but faces challenges in the readiness of its market and in the supply of high-quality applications. HFE has a unique combination of three fundamental characteristics: (1) it takes a systems approach (2) it is design driven and (3) it focuses on two closely related outcomes: performance and well-being. In order to contribute to future system design, HFE must demonstrate its value more successfully to the main stakeholders of system design. HFE already has a strong value proposition (mainly well-being) and interactivity with the stakeholder group of 'system actors' (employees and product/service users). However, the value proposition (mainly performance) and relationships with the stakeholder groups of 'system experts' (experts fromtechnical and social sciences involved in system design), and 'system decision makers' (managers and other decision makers involved in system design, purchase, implementation and use), who have a strong power to influence system design, need to be developed. Therefore, the first main strategic direction is to strengthen the demand for high-quality HFE by increasing awareness among powerful stakeholders of the value of high-quality HFE by communicating with stakeholders, by building partnerships and by educating stakeholders. The second main strategic direction is to strengthen the application of high-quality HFE by promoting the education of HFE specialists, by ensuring high-quality standards of HFE applications and HFE specialists, and by promoting HFE research excellence at universities and other organisations. This strategy requires cooperation between the HFE community at large, consisting of the International Ergonomics Association (IEA), local (national and regional) HFE societies, and HFE specialists. We propose a joint world-wide HFE development plan, in which the IEA takes a leadership role. Human factors/ergonomics (HFE) has much to offer by addressing major business and societal challenges regarding work and product/service systems. HFE potential, however, is underexploited. This paper presents a strategy for the HFE community to strengthen demand and application of high-quality HFE, emphasising its key elements: systems approach, design driven, and performance and well-being goals.

Expert System Application of Forward Chaining and Certainty Factors Method for The Decision of Contraception Tools

NASA Astrophysics Data System (ADS)

Prambudi, Dwi Arief; Widodo, Catur Edi; Widodo, Aris Puji

2018-02-01

The choice of contraceptive tools is not an easy thing because the risks or effects will give impact on the body that never using it previously. in the other side, there is no contraception always suit for everybody because the circumstances of each body is different, so the extensive knowledge must be needed to know the advantages and disadvantages of each contraceptive tools then adjusted to the user's body.The expert system for contraceptive tools uses Forward Chaining search method combined with Certainty Factors Method. These method value the patient's indication. The Expert system gives the output data which define the kind of tool uses of the patient. the results obtained will be able to help people to find indications that lead to appropriate contraceptive tools and advice or suggestions about these tools. The success rate of the contraceptive tools decision experienced by experienced by the user by using forward chaining combined with the CF computation method is also influenced by the number of indication criteria selected by the user. Based on testing that has been done, expert system contraception tools has accuracy level equal to 75%.

Supplemental knowledge acquisition through external product interface for CLIPS

NASA Technical Reports Server (NTRS)

Saito, Tim; Ebaud, Stephen; Loftin, Bowen R.

1990-01-01

Traditionally, the acquisition of knowledge for expert systems consisted of the interview process with the domain or subject matter expert (SME), observation of domain environment, and information gathering and research which constituted a direct form of knowledge acquisition (KA). The knowledge engineer would be responsible for accumulating pertinent information and/or knowledge from the SME(s) for input into the appropriate expert system development tool. The direct KA process may (or may not) have included forms of data or documentation to incorporate from the SME's surroundings. The differentiation between direct KA and supplemental KA (indirect) would be the difference in the use of data. In acquiring supplemental knowledge, the knowledge engineer would access other types of evidence (manuals, documents, data files, spreadsheets, etc.) that would support the reasoning or premises of the SME. When an expert makes a decision in a particular task, one tool that may have been used to justify a recommendation, would have been a spreadsheet total or column figure. Locating specific decision points from that data within the SME's framework would constitute supplemental KA. Data used for a specific purpose in one system or environment would be used as supplemental knowledge for another, specifically a CLIPS project.

Ethical evaluation of research proposals by ethics panels advising the European Commission.

PubMed

Kolar, Roman

2004-06-01

Ethical principles with regard to animal experimentation are referred to in European Union (EU) legislation and other official documents. Therefore, applications for funding of research under the EU's research programme may undergo an ethical review that is carried out by so-called ethics panels, consisting of experts chosen by the European Commission. The work of these panels differs substantially from that of other ethical committees, as they exist on the institutional, local, regional or national level. Their main purpose is not to decide whether a proposed research can be regarded legal, and therefore should be endorsed or licensed; instead, it is to help the Commission in prioritising its funding. The panels may examine other ethical aspects than those of animal experimentation or animal welfare alone, such as the use of human volunteers. This is reflected by the composition of the panels. Their decisions are normally based on consensus. Even though these decisions may refer to EU legislation, the criteria applied are not restricted to those provided by this legislation. Nevertheless, the various aspects of the Commission's ethical evaluation system (e.g. formal and practical basic conditions, information content of applications, type of decisions taken, lacking of any quality control) offers opportunities for improvement.

Dypas: A dynamic payload scheduler for shuttle missions

NASA Technical Reports Server (NTRS)

Davis, Stephen

1988-01-01

Decision and analysis systems have had broad and very practical application areas in the human decision making process. These software systems range from the help sections in simple accounting packages, to the more complex computer configuration programs. Dypas is a decision and analysis system that aids prelaunch shutlle scheduling, and has added functionality to aid the rescheduling done in flight. Dypas is written in Common Lisp on a Symbolics Lisp machine. Dypas differs from other scheduling programs in that it can draw its knowledge from different rule bases and apply them to different rule interpretation schemes. The system has been coded with Flavors, an object oriented extension to Common Lisp on the Symbolics hardware. This allows implementation of objects (experiments) to better match the problem definition, and allows a more coherent solution space to be developed. Dypas was originally developed to test a programmer's aptitude toward Common Lisp and the Symbolics software environment. Since then the system has grown into a large software effort with several programmers and researchers thrown into the effort. Dypas is currently using two expert systems and three inferencing procedures to generate a many object schedule. The paper will review the abilities of Dypas and comment on its functionality.

A structured approach to Exposure Based Waiving of human health endpoints under REACH developed in the OSIRIS project.

PubMed

Marquart, Hans; Meijster, Tim; Van de Bovenkamp, Marja; Ter Burg, Wouter; Spaan, Suzanne; Van Engelen, Jacqueline

2012-03-01

Exposure Based Waiving (EBW) is one of the options in REACH when there is insufficient hazard data on a specific endpoint. Rules for adaptation of test requirements are specified and a general option for EBW is given via Appendix XI of REACH, allowing waiving of repeated dose toxicity studies, reproductive toxicity studies and carcinogenicity studies under a number of conditions if exposure is very low. A decision tree is described that was developed in the European project OSIRIS (Optimised Strategies for Risk Assessment of Industrial Chemicals through Integration of Non-Test and Test Information) to help decide in what cases EBW can be justified. The decision tree uses specific criteria as well as more general questions. For the latter, guidance on interpretation and resulting conclusions is provided. Criteria and guidance are partly based on an expert elicitation process. Among the specific criteria a number of proposed Thresholds of Toxicological Concern are used. The decision tree, expanded with specific parts on absorption, distribution, metabolism and excretion that are not described in this paper, is implemented in the OSIRIS webtool on integrated testing strategies. Copyright © 2011 Elsevier Inc. All rights reserved.

Clinical Ethics Consultants are not “Ethics” Experts—But They do Have Expertise 1

PubMed Central

Rasmussen, Lisa M.

2016-01-01

The attempt to critique the profession of clinical ethics consultation by establishing the impossibility of ethics expertise has been a red herring. Decisions made in clinical ethics cases are almost never based purely on moral judgments. Instead, they are all-things-considered judgments that involve determining how to balance other values as well. A standard of justified decision-making in this context would enable us to identify experts who could achieve these standards more often than others, and thus provide a basis for expertise in clinical ethics consultation. This expertise relies in part on what Richard Zaner calls the “expert knowledge of ethical phenomena” (1988, 8). PMID:27302970

Aeromedical decision making--it may be time for a paradigm change.

PubMed

Steinkraus, Lawrence W; Rayman, Russell B; Butler, William P; Marsh, Royden W; Ercoline, William; Cowl, Clayton T

2012-10-01

Recent events in the U-2 and F-22 fleets have challenged aeromedical experts, highlighting the need for better in-flight aircrew physiologic and cognitive monitoring capability. Existing aerospace medicine risk assessment tools, while necessary, are no longer sufficient to affect positive safety changes given the evolving nature of the aerospace environment. Cognition and its sub-elements are now primary measures for the "Fit to Fly" decision. We must investigate practical methodologies for determining dynamic aircrew physiologic and cognitive function preflight (selection, retention) and in-flight (selection, retention, performance enhancement). In 2010, a panel of aeromedical experts met to address current paradigms and suggest possible solutions. This commentary briefly summarizes panel findings and recommendations.

Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

NASA Astrophysics Data System (ADS)

Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

2016-09-01

In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

Pharmacy executives: leadership issues and associated skills, knowledge, and abilities in the U.S. Department of Defense.

PubMed

Meadows, Andrew B; Finstuen, Kenn; Hudak, Ronald P

2003-01-01

To identify the issues or problems that current and aspiring U.S. Department of Defense (DoD) pharmacy executives will face in the future and to define the skills, knowledge, and abilities (SKAs) required to successfully address these issues. Delphi method for executive decision making. DoD. Ninety-three pharmacists serving in the military grades of lieutenant colonel/commander and colonel/captain, as well as pharmacists selected for promotion to those grades. iterations of the Delphi method for executive decision making separated by an expert panel content analysis. Round 1--participants identified five major issues believed to be of greatest importance to pharmacy executives and reported specific SKAs that might be needed to successfully manage those issues. An expert panel sorted these issues into meaningful domains, then provided an appropriate title for each domain. Round 2--on a 7-point scale, respondents rated the SKA items according to their assessment of how much a future DoD pharmacy executive would need each SKA. Response rates were 44.1% and 46.2% for Delphi rounds 1 and 2, respectively. The first round generated 62 unique issues facing pharmacy executives. The expert panel reviewed and sorted the issues into eight domains and selected an appropriate title for each domain. The domains identified by the panel were human resources, pharmacy operations/business practices, information management and technology, financial resources, formulary management, drug therapy management, pharmacy benefit management, and leadership. During round 2, 73.3% of the top 15 rated SKAs came from the drug therapy management, leadership, and formulary management domains. The three highest-rated SKAs were "ability to see the big picture," "ability to build strong relations with medical staffs," and "skills in both writing and verbal communication." The issues facing future DoD pharmacy executives will require them to expand their clinical abilities as well as their ability to collaborate and communicate with other professionals.

Formal analysis of the surgical pathway and development of a new software tool to assist surgeons in the decision making in primary breast surgery.

PubMed

Catanuto, Giuseppe; Pappalardo, Francesco; Rocco, Nicola; Leotta, Marco; Ursino, Venera; Chiodini, Paolo; Buggi, Federico; Folli, Secondo; Catalano, Francesca; Nava, Maurizio B

2016-10-01

The increased complexity of the decisional process in breast cancer surgery is well documented. With this study we aimed to create a software tool able to assist patients and surgeons in taking proper decisions. We hypothesized that the endpoints of breast cancer surgery could be addressed combining a set of decisional drivers. We created a decision support system software tool (DSS) and an interactive decision tree. A formal analysis estimated the information gain derived from each feature in the process. We tested the DSS on 52 patients and we analyzed the concordance of decisions obtained by different users and between the DSS suggestions and the actual surgery. We also tested the ability of the system to prevent post breast conservation deformities. The information gain revealed that patients preferences are the root of our decision tree. An observed concordance respectively of 0.98 and 0.88 was reported when the DSS was used twice by an expert operator or by a newly trained operator vs. an expert one. The observed concordance between the DSS suggestion and the actual decision was 0.69. A significantly higher incidence of post breast conservation defects was reported among patients who did not follow the DSS decision (Type III of Fitoussi, N = 4; 33.3%, p = 0.004). The DSS decisions can be reproduced by operators with different experience. The concordance between suggestions and actual decision is quite low, however the DSS is able to prevent post- breast conservation deformities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development and acceptability testing of decision trees for self-management of prosthetic socket fit in adults with lower limb amputation.

PubMed

Lee, Daniel Joseph; Veneri, Diana A

2018-05-01

The most common complaint lower limb prosthesis users report is inadequacy of a proper socket fit. Adjustments to the residual limb-socket interface can be made by the prosthesis user without consultation of a clinician in many scenarios through skilled self-management. Decision trees guide prosthesis wearers through the self-management process, empowering them to rectify fit issues, or referring them to a clinician when necessary. This study examines the development and acceptability testing of patient-centered decision trees for lower limb prosthesis users. Decision trees underwent a four-stage process: literature review and expert consultation, designing, two-rounds of expert panel review and revisions, and target audience testing. Fifteen lower limb prosthesis users (average age 61 years) reviewed the decision trees and completed an acceptability questionnaire. Participants reported agreement of 80% or above in five of the eight questions related to acceptability of the decision trees. Disagreement was related to the level of experience of the respondent. Decision trees were found to be easy to use, illustrate correct solutions to common issues, and have terminology consistent with that of a new prosthesis user. Some users with greater than 1.5 years of experience would not use the decision trees based on their own self-management skills. Implications for Rehabilitation Discomfort of the residual limb-prosthetic socket interface is the most common reason for clinician visits. Prosthesis users can use decision trees to guide them through the process of obtaining a proper socket fit independently. Newer users may benefit from using the decision trees more than experienced users.

Communication about colorectal cancer screening in Britain: public preferences for an expert recommendation.

PubMed

Waller, J; Macedo, A; von Wagner, C; Simon, A E; Jones, C; Hammersley, V; Weller, D; Wardle, J; Campbell, C

2012-12-04

Informed decision-making approaches to cancer screening emphasise the importance of decisions being determined by individuals' own values and preferences. However, advice from a trusted source may also contribute to autonomous decision-making. This study examined preferences regarding a recommendation from the NHS and information provision in the context of colorectal cancer (CRC) screening. In face-to-face interviews, a population-based sample of adults across Britain (n=1964; age 50-80 years) indicated their preference between: (1) a strong recommendation to participate in CRC screening, (2) a recommendation alongside advice to make an individual decision, and (3) no recommendation but advice to make an individual decision. Other measures included trust in the NHS and preferences for information on benefits and risks. Most respondents (84%) preferred a recommendation (47% strong recommendation, 37% recommendation plus individual decision-making advice), but the majority also wanted full information on risks (77%) and benefits (78%). Men were more in favour of a recommendation than women (86% vs 81%). Trust in the NHS was high overall, but the minority who expressed low trust were less likely to want a recommendation. Most British adults want full information on risks and benefits of screening but they also want a recommendation from an authoritative source. An 'expert' view may be an important part of autonomous health decision-making.

A genetic algorithms approach for altering the membership functions in fuzzy logic controllers

NASA Technical Reports Server (NTRS)

Shehadeh, Hana; Lea, Robert N.

1992-01-01

Through previous work, a fuzzy control system was developed to perform translational and rotational control of a space vehicle. This problem was then re-examined to determine the effectiveness of genetic algorithms on fine tuning the controller. This paper explains the problems associated with the design of this fuzzy controller and offers a technique for tuning fuzzy logic controllers. A fuzzy logic controller is a rule-based system that uses fuzzy linguistic variables to model human rule-of-thumb approaches to control actions within a given system. This 'fuzzy expert system' features rules that direct the decision process and membership functions that convert the linguistic variables into the precise numeric values used for system control. Defining the fuzzy membership functions is the most time consuming aspect of the controller design. One single change in the membership functions could significantly alter the performance of the controller. This membership function definition can be accomplished by using a trial and error technique to alter the membership functions creating a highly tuned controller. This approach can be time consuming and requires a great deal of knowledge from human experts. In order to shorten development time, an iterative procedure for altering the membership functions to create a tuned set that used a minimal amount of fuel for velocity vector approach and station-keep maneuvers was developed. Genetic algorithms, search techniques used for optimization, were utilized to solve this problem.

Predicting soccer matches after unconscious and conscious thought as a function of expertise.

PubMed

Dijksterhuis, Ap; Bos, Maarten W; van der Leij, Andries; van Baaren, Rick B

2009-11-01

In two experiments, we investigated the effects of expertise and mode of thought on the accuracy of people's predictions. Both experts and nonexperts predicted the results of soccer matches after conscious thought, after unconscious thought, or immediately. In Experiment 1, experts who thought unconsciously outperformed participants in all other conditions. Whereas unconscious thinkers showed a correlation between expertise and accuracy of prediction, no such relation was observed for conscious thinkers or for immediate decision makers. In Experiment 2, this general pattern was replicated. In addition, experts who thought unconsciously were better at applying diagnostic information than experts who thought consciously or who decided immediately. The results are consistent with unconscious-thought theory.

Intelligent system for topic survey in MEDLINE by keyword recommendation and learning text characteristics.

PubMed

Tanaka, M; Nakazono, S; Matsuno, H; Tsujimoto, H; Kitamura, Y; Miyano, S

2000-01-01

We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.

Supervised multimedia categorization

NASA Astrophysics Data System (ADS)

Aldershoff, Frank; Salden, Alfons H.; Iacob, Sorin M.; Kempen, Masja

2003-01-01

Static multimedia on the Web can already be hardly structured manually. Although unavoidable and necessary, manual annotation of dynamic multimedia becomes even less feasible when multimedia quickly changes in complexity, i.e. in volume, modality, and usage context. The latter context could be set by learning or other purposes of the multimedia material. This multimedia dynamics calls for categorisation systems that index, query and retrieve multimedia objects on the fly in a similar way as a human expert would. We present and demonstrate such a supervised dynamic multimedia object categorisation system. Our categorisation system comes about by continuously gauging it to a group of human experts who annotate raw multimedia for a certain domain ontology given a usage context. Thus effectively our system learns the categorisation behaviour of human experts. By inducing supervised multi-modal content and context-dependent potentials our categorisation system associates field strengths of raw dynamic multimedia object categorisations with those human experts would assign. After a sufficient long period of supervised machine learning we arrive at automated robust and discriminative multimedia categorisation. We demonstrate the usefulness and effectiveness of our multimedia categorisation system in retrieving semantically meaningful soccer-video fragments, in particular by taking advantage of multimodal and domain specific information and knowledge supplied by human experts.

Discussing uncertainty and risk in primary care: recommendations of a multi-disciplinary panel regarding communication around prostate cancer screening.

PubMed

Wilkes, Michael; Srinivasan, Malathi; Cole, Galen; Tardif, Richard; Richardson, Lisa C; Plescia, Marcus

2013-11-01

Shared decision making improves value-concordant decision-making around prostate cancer screening (PrCS). Yet, PrCS discussions remain complex, challenging and often emotional for physicians and average-risk men. In July 2011, the Centers for Disease Control and Prevention convened a multidisciplinary expert panel to identify priorities for funding agencies and development groups to promote evidence-based, value-concordant decisions between men at average risk for prostate cancer and their physicians. Two-day multidisciplinary expert panel in Atlanta, Georgia, with structured discussions and formal consensus processes. Sixteen panelists represented diverse specialties (primary care, medical oncology, urology), disciplines (sociology, communication, medical education, clinical epidemiology) and market sectors (patient advocacy groups, Federal funding agencies, guideline-development organizations). Panelists used guiding interactional and evaluation models to identify and rate strategies that might improve PrCS discussions and decisions for physicians, patients and health systems/society. Efficacy was defined as the likelihood of each strategy to impact outcomes. Effort was defined as the relative amount of effort to develop, implement and sustain the strategy. Each strategy was rated (1-7 scale; 7 = maximum) using group process software (ThinkTank(TM)). For each group, intervention strategies were grouped as financial/regulatory, educational, communication or attitudinal levers. For each strategy, barriers were identified. Highly ranked strategies to improve value-concordant shared decision-making (SDM) included: changing outpatient clinic visit reimbursement to reward SDM; development of evidence-based, technology-assisted, point-of-service tools for physicians and patients; reframing confusing prostate cancer screening messages; providing pre-visit decision support interventions; utilizing electronic health records to promote benchmarking/best practices; providing additional training for physicians around value-concordant decision-making; and using re-accreditation to promote training. Conference outcomes present an expert consensus of strategies likely to improve value-concordant prostate cancer screening decisions. In addition, the methodology used to obtain agreement provides a model of successful collaboration around this and future controversial cancer screening issues, which may be of interest to funding agencies, educators and policy makers.

Development of Seasonal Influenza Vaccination Recommendations: Relevance and Influence of the Evidence on the Decision-Making Process in France and the Netherlands.

PubMed

Silva, Maria Laura; Paget, W John; Mosnier, Anne; Buthion, Valérie; Cohen, Jean Marie; Perrier, Lionel; Späth, Hans Martin

2016-01-01

Target groups for seasonal influenza vaccination are defined at the country level and are based on several factors. However, little is known about the national decision-making procedures. The purpose of this study was to compare the evidence used for the development of recommendations and its impact on the choice of target groups in France and the Netherlands. A preliminary documentary analysis identified institutions to include in the assessment: governmental authorities, research institutions, associations, and manufacturers. At least one expert from each group was invited to our study. Thirty-three semi-structured interviews were conducted in 2013 (16 France, 17 the Netherlands). We used NVivo10® to perform a thematic content analysis. Clinical/epidemiological studies were the evidence most used in both countries. Economic models were increasingly being used; these had greater influence on the decision making in the Netherlands than in France, probably because of the presence of a modeler. Generally, the quality of the evidence used was poor, although no systematic use of standard protocol for its assessment was observed. A general protocol was sometimes used in France; however, the personal judgment of the experts was crucial for the assessment in both countries. There were differences in the target groups, for example, pregnant women, recommended only in France. France and the Netherlands use similar evidence for developing vaccination recommendations, although different decisions are sometimes made regarding target groups. This could be associated with the lack of systematic standard appraisals, increasing the influence of the experts' judgment on decision making. The development of standards for the appraisal of evidence is recommended. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Report [of the] Expert Meeting on Intercultural Education, Section of Education for Peace and Human Rights (UNESCO Headquarters, Paris, March 20-22, 2006)

ERIC Educational Resources Information Center

United Nations Educational, Scientific and Cultural Organization (UNESCO), 2006

2006-01-01

The Section of Education for Peace and Human Rights of the Division for the Promotion of Quality Education held an expert meeting on Intercultural Education from March 20-22, 2006 at UNESCO Headquarters, bringing together international experts from Australia, Bolivia, Egypt, Finland, Hungary, Korea, Lebanon, Mexico, Nigeria, South Africa and the…

Extension of Companion Modeling Using Classification Learning

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Bousquet, François; Ishida, Toru

Companion Modeling is a methodology of refining initial models for understanding reality through a role-playing game (RPG) and a multiagent simulation. In this research, we propose a novel agent model construction methodology in which classification learning is applied to the RPG log data in Companion Modeling. This methodology enables a systematic model construction that handles multi-parameters, independent of the modelers ability. There are three problems in applying classification learning to the RPG log data: 1) It is difficult to gather enough data for the number of features because the cost of gathering data is high. 2) Noise data can affect the learning results because the amount of data may be insufficient. 3) The learning results should be explained as a human decision making model and should be recognized by the expert as being the result that reflects reality. We realized an agent model construction system using the following two approaches: 1) Using a feature selction method, the feature subset that has the best prediction accuracy is identified. In this process, the important features chosen by the expert are always included. 2) The expert eliminates irrelevant features from the learning results after evaluating the learning model through a visualization of the results. Finally, using the RPG log data from the Companion Modeling of agricultural economics in northeastern Thailand, we confirm the capability of this methodology.

An evidence-based approach to interactive health communication: a challenge to medicine in the information age. Science Panel on Interactive Communication and Health.

PubMed

Robinson, T N; Patrick, K; Eng, T R; Gustafson, D

1998-10-14

To examine the current status of interactive health communication (IHC) and propose evidence-based approaches to improve the quality of such applications. The Science Panel on Interactive Communication and Health, a 14-member, nonfederal panel with expertise in clinical medicine and nursing, public health, media and instructional design, health systems engineering, decision sciences, computer and communication technologies, and health communication, convened by the Office of Disease Prevention and Health Promotion, US Department of Health and Human Services. Published studies, online resources, expert panel opinions, and opinions from outside experts in fields related to IHC. The panel met 9 times during more than 2 years. Government agencies and private-sector experts provided review and feedback on the panel's work. Interactive health communication applications have great potential to improve health, but they may also cause harm. To date, few applications have been adequately evaluated. Physicians and other health professionals should promote and participate in an evidence-based approach to the development and diffusion of IHC applications and endorse efforts to rigorously evaluate the safety, quality, and utility of these resources. A standardized reporting template is proposed to help developers and evaluators of IHC applications conduct evaluations and disclose their results and to help clinicians, purchasers, and consumers judge the quality of IHC applications.

A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

NASA Astrophysics Data System (ADS)

Zhang, Wancheng; Xu, Yejun; Wang, Huimin

2016-01-01

The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making (MAGDM) problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.

The Paradox of Expertise.

ERIC Educational Resources Information Center

Hankins, George.

1987-01-01

Describes the novice-to-expert model of human learning and compares it to the recent advances in the areas of artificial intelligence and expert systems. Discusses some of the characteristics of experts, proposing connections between them with expert systems and theories of left-right brain functions. (TW)

Educating Jurors about Forensic Evidence: Using an Expert Witness and Judicial Instructions to Mitigate the Impact of Invalid Forensic Science Testimony.

PubMed

Eastwood, Joseph; Caldwell, Jiana

2015-11-01

Invalid expert witness testimony that overstated the precision and accuracy of forensic science procedures has been highlighted as a common factor in many wrongful conviction cases. This study assessed the ability of an opposing expert witness and judicial instructions to mitigate the impact of invalid forensic science testimony. Participants (N = 155) acted as mock jurors in a sexual assault trial that contained both invalid forensic testimony regarding hair comparison evidence, and countering testimony from either a defense expert witness or judicial instructions. Results showed that the defense expert witness was successful in educating jurors regarding limitations in the initial expert's conclusions, leading to a greater number of not-guilty verdicts. The judicial instructions were shown to have no impact on verdict decisions. These findings suggest that providing opposing expert witnesses may be an effective safeguard against invalid forensic testimony in criminal trials. © 2015 American Academy of Forensic Sciences.

The role of central and peripheral vision in expert decision making.

PubMed

Ryu, Donghyun; Abernethy, Bruce; Mann, David L; Poolton, Jamie M; Gorman, Adam D

2013-01-01

The purpose of this study was to investigate the role of central and peripheral vision in expert decision making. A gaze-contingent display was used to selectively present information to the central and peripheral areas of the visual field while participants performed a decision-making task. Eleven skilled and eleven less-skilled male basketball players watched video clips of basketball scenarios in three different viewing conditions: full-image control, moving window (central vision only), and moving mask (peripheral vision only). At the conclusion of each clip participants were required to decide whether it was more appropriate for the ball-carrier to pass the ball or to drive to the basket. The skilled players showed significantly higher response accuracy and faster response times compared with their lesser-skilled counterparts in all three viewing conditions, demonstrating superiority in information extraction that held irrespective of whether they were using central or peripheral vision. The gaze behaviour of the skilled players was less influenced by the gaze-contingent manipulations, suggesting they were better able to use the remaining information to sustain their normal gaze behaviour. The superior capacity of experts to interpret dynamic visual information is evident regardless of whether the visual information is presented across the whole visual field or selectively to either central or peripheral vision alone.

Assessing experience in the deliberate practice of running using a fuzzy decision-support system

PubMed Central

Roveri, Maria Isabel; Manoel, Edison de Jesus; Onodera, Andrea Naomi; Ortega, Neli R. S.; Tessutti, Vitor Daniel; Vilela, Emerson; Evêncio, Nelson

2017-01-01

The judgement of skill experience and its levels is ambiguous though it is crucial for decision-making in sport sciences studies. We developed a fuzzy decision support system to classify experience of non-elite distance runners. Two Mamdani subsystems were developed based on expert running coaches’ knowledge. In the first subsystem, the linguistic variables of training frequency and volume were combined and the output defined the quality of running practice. The second subsystem yielded the level of running experience from the combination of the first subsystem output with the number of competitions and practice time. The model results were highly consistent with the judgment of three expert running coaches (r>0.88, p<0.001) and also with five other expert running coaches (r>0.86, p<0.001). From the expert’s knowledge and the fuzzy model, running experience is beyond the so-called "10-year rule" and depends not only on practice time, but on the quality of practice (training volume and frequency) and participation in competitions. The fuzzy rule-based model was very reliable, valid, deals with the marked ambiguities inherent in the judgment of experience and has potential applications in research, sports training, and clinical settings. PMID:28817655

When does atopic dermatitis warrant systemic therapy? Recommendations from an expert panel of the International Eczema Council.

PubMed

Simpson, Eric L; Bruin-Weller, Marjolein; Flohr, Carsten; Ardern-Jones, Michael R; Barbarot, Sebastien; Deleuran, Mette; Bieber, Thomas; Vestergaard, Christian; Brown, Sara J; Cork, Michael J; Drucker, Aaron M; Eichenfield, Lawrence F; Foelster-Holst, Regina; Guttman-Yassky, Emma; Nosbaum, Audrey; Reynolds, Nick J; Silverberg, Jonathan I; Schmitt, Jochen; Seyger, Marieke M B; Spuls, Phyllis I; Stalder, Jean-Francois; Su, John C; Takaoka, Roberto; Traidl-Hoffmann, Claudia; Thyssen, Jacob P; van der Schaft, Jorien; Wollenberg, Andreas; Irvine, Alan D; Paller, Amy S

2017-10-01

Although most patients with atopic dermatitis (AD) are effectively managed with topical medication, a significant minority require systemic therapy. Guidelines for decision making about advancement to systemic therapy are lacking. To guide those considering use of systemic therapy in AD and provide a framework for evaluation before making this therapeutic decision with the patient. A subgroup of the International Eczema Council determined aspects to consider before prescribing systemic therapy. Topics were assigned to expert reviewers who performed a topic-specific literature review, referred to guidelines when available, and provided interpretation and expert opinion. We recommend a systematic and holistic approach to assess patients with severe signs and symptoms of AD and impact on quality of life before systemic therapy. Steps taken before commencing systemic therapy include considering alternate or concomitant diagnoses, avoiding trigger factors, optimizing topical therapy, ensuring adequate patient/caregiver education, treating coexistent infection, assessing the impact on quality of life, and considering phototherapy. Our work is a consensus statement, not a systematic review. The decision to start systemic medication should include assessment of severity and quality of life while considering the individual's general health status, psychologic needs, and personal attitudes toward systemic therapies. Copyright © 2017 American Academy of Dermatology, Inc. All rights reserved.

Mobile app for human-interaction with sitter robots

NASA Astrophysics Data System (ADS)

Das, Sumit Kumar; Sahu, Ankita; Popa, Dan O.

2017-05-01

Human environments are often unstructured and unpredictable, thus making the autonomous operation of robots in such environments is very difficult. Despite many remaining challenges in perception, learning, and manipulation, more and more studies involving assistive robots have been carried out in recent years. In hospital environments, and in particular in patient rooms, there are well-established practices with respect to the type of furniture, patient services, and schedule of interventions. As a result, adding a robot into semi-structured hospital environments is an easier problem to tackle, with results that could have positive benefits to the quality of patient care and the help that robots can offer to nursing staff. When working in a healthcare facility, robots need to interact with patients and nurses through Human-Machine Interfaces (HMIs) that are intuitive to use, they should maintain awareness of surroundings, and offer safety guarantees for humans. While fully autonomous operation for robots is not yet technically feasible, direct teleoperation control of the robot would also be extremely cumbersome, as it requires expert user skills, and levels of concentration not available to many patients. Therefore, in our current study we present a traded control scheme, in which the robot and human both perform expert tasks. The human-robot communication and control scheme is realized through a mobile tablet app that can be customized for robot sitters in hospital environments. The role of the mobile app is to augment the verbal commands given to a robot through natural speech, camera and other native interfaces, while providing failure mode recovery options for users. Our app can access video feed and sensor data from robots, assist the user with decision making during pick and place operations, monitor the user health over time, and provides conversational dialogue during sitting sessions. In this paper, we present the software and hardware framework that enable a patient sitter HMI, and we include experimental results with a small number of users that demonstrate that the concept is sound and scalable.

Using Hierarchical Cluster Models to Systematically Identify Groups of Jobs With Similar Occupational Questionnaire Response Patterns to Assist Rule-Based Expert Exposure Assessment in Population-Based Studies

PubMed Central

Friesen, Melissa C.; Shortreed, Susan M.; Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Silverman, Debra T.; Yu, Kai

2015-01-01

Objectives: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Methods: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m−3 respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters’ homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job’s estimate and the mean estimate for all jobs within the cluster. Results: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. Conclusions: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. PMID:25477475

Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies.

PubMed

Friesen, Melissa C; Shortreed, Susan M; Wheeler, David C; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S; Baris, Dalsu; Karagas, Margaret R; Schwenn, Molly; Johnson, Alison; Armenti, Karla R; Silverman, Debra T; Yu, Kai

2015-05-01

Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster. Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.

Should this event be notified to the World Health Organization? Reliability of the international health regulations notification assessment process.

PubMed

Haustein, Thomas; Hollmeyer, Helge; Hardiman, Max; Harbarth, Stephan; Pittet, Didier

2011-04-01

To investigate the reliability of the public health event notification assessment process under the International Health Regulations (2005) (IHR). In 2009, 193 National IHR Focal Points (NFPs) were invited to use the decision instrument in Annex 2 of the IHR to determine whether 10 fictitious public health events should be notified to WHO. Each event's notifiability was assessed independently by an expert panel. The degree of consensus among NFPs and of concordance between NFPs and the expert panel was considered high when more than 70% agreed on a response. Overall, 74% of NFPs responded. The median degree of consensus among NFPs on notification decisions was 78%. It was high for the six events considered notifiable by the majority (median: 80%; range: 76-91) but low for the remaining four (median: 55%; range: 54-60). The degree of concordance between NFPs and the expert panel was high for the five events deemed notifiable by the panel (median: 82%; range: 76-91) but low (median: 51%; range: 42-60) for those not considered notifiable. The NFPs identified notifiable events with greater sensitivity than specificity (P < 0.001). When used by NFPs, the notification assessment process in Annex 2 of the IHR was sensitive in identifying public health events that were considered notifiable by an expert panel, but only moderately specific. The reliability of the assessments could be increased by expanding guidance on the use of the decision instrument and by including more specific criteria for assessing events and clearer definitions of terms.

Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge

PubMed Central

2012-01-01

Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475

Assessing clinical reasoning (ASCLIRE): Instrument development and validation.

PubMed

Kunina-Habenicht, Olga; Hautz, Wolf E; Knigge, Michel; Spies, Claudia; Ahlers, Olaf

2015-12-01

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the entire clinical decision process. In a cross-sectional study participants were asked to choose as many diagnostic measures as they deemed necessary to diagnose the underlying disease of six different cases with acute or sub-acute dyspnea and provide a diagnosis. 283 students and 20 content experts participated. In addition to diagnostic accuracy, respective decision time and number of used relevant diagnostic measures were documented as distinct performance indicators. The empirical structure of the test was investigated using a structural equation modeling approach. Experts showed higher accuracy rates and lower decision times than students. In a cross-sectional comparison, the diagnostic accuracy of students improved with the year of study. Wrong diagnoses provided by our sample were comparable to wrong diagnoses in practice. We found an excellent fit for a model with three latent factors-diagnostic accuracy, decision time, and choice of relevant diagnostic information-with diagnostic accuracy showing no significant correlation with decision time. ASCLIRE considers decision time as an important performance indicator beneath diagnostic accuracy and provides evidence that clinical reasoning is a complex ability comprising diagnostic accuracy, decision time, and choice of relevant diagnostic information as three partly correlated but still distinct aspects.