Science.gov

Sample records for rule-based decision support

  1. An HL7-CDA wrapper for facilitating semantic interoperability to rule-based Clinical Decision Support Systems.

    PubMed

    Sáez, Carlos; Bresó, Adrián; Vicente, Javier; Robles, Montserrat; García-Gómez, Juan Miguel

    2013-03-01

    The success of Clinical Decision Support Systems (CDSS) greatly depends on its capability of being integrated in Health Information Systems (HIS). Several proposals have been published up to date to permit CDSS gathering patient data from HIS. Some base the CDSS data input on the HL7 reference model, however, they are tailored to specific CDSS or clinical guidelines technologies, or do not focus on standardizing the CDSS resultant knowledge. We propose a solution for facilitating semantic interoperability to rule-based CDSS focusing on standardized input and output documents conforming an HL7-CDA wrapper. We define the HL7-CDA restrictions in a HL7-CDA implementation guide. Patient data and rule inference results are mapped respectively to and from the CDSS by means of a binding method based on an XML binding file. As an independent clinical document, the results of a CDSS can present clinical and legal validity. The proposed solution is being applied in a CDSS for providing patient-specific recommendations for the care management of outpatients with diabetes mellitus. PMID:23199936

  2. Knowledge-based systems as decision support tools in an ecosystem approach to fisheries: Comparing a fuzzy-logic and a rule-based approach

    NASA Astrophysics Data System (ADS)

    Jarre, Astrid; Paterson, Barbara; Moloney, Coleen L.; Miller, David C. M.; Field, John G.; Starfield, Anthony M.

    2008-10-01

    In an ecosystem approach to fisheries (EAF), management must draw on information of widely different types, and information addressing various scales. Knowledge-based systems assist in the decision-making process by summarising this information in a logical, transparent and reproducible way. Both rule-based Boolean and fuzzy-logic models have been used successfully as knowledge-based decision support tools. This study compares two such systems relevant to fisheries management in an EAF developed for the southern Benguela. The first is a rule-based system for the prediction of anchovy recruitment and the second is a fuzzy-logic tool to monitor implementation of an EAF in the sardine fishery. We construct a fuzzy-logic counterpart to the rule-based model, and a rule-based counterpart to the fuzzy-logic model, compare their results, and include feedback from potential users of these two decision support tools in our evaluation of the two approaches. With respect to the model objectives, no method clearly outperformed the other. The advantages of numerically processing continuous variables, and interpreting the final output, as in fuzzy-logic models, can be weighed up against the advantages of using a few, qualitative, easy-to-understand categories as in rule-based models. The natural language used in rule-based implementations is easily understood by, and communicated among, users of these systems. Users unfamiliar with fuzzy-set theory must “trust” the logic of the model. Graphical visualization of intermediate and end results is an important advantage of any system. Applying the two approaches in parallel improved our understanding of the model as well as of the underlying problems. Even for complex problems, small knowledge-based systems such as the ones explored here are worth developing and using. Their strengths lie in (i) synthesis of the problem in a logical and transparent framework, (ii) helping scientists to deliberate how to apply their science to

  3. 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

  4. On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

    NASA Technical Reports Server (NTRS)

    Tunstel, Edward; Jamshidi, Mo

    1997-01-01

    Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

  5. A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler.

    PubMed

    Butt, Muhammad Arif; Akram, Muhammad

    2016-01-01

    We present a new intuitionistic fuzzy rule-based decision-making system based on intuitionistic fuzzy sets for a process scheduler of a batch operating system. Our proposed intuitionistic fuzzy scheduling algorithm, inputs the nice value and burst time of all available processes in the ready queue, intuitionistically fuzzify the input values, triggers appropriate rules of our intuitionistic fuzzy inference engine and finally calculates the dynamic priority (dp) of all the processes in the ready queue. Once the dp of every process is calculated the ready queue is sorted in decreasing order of dp of every process. The process with maximum dp value is sent to the central processing unit for execution. Finally, we show complete working of our algorithm on two different data sets and give comparisons with some standard non-preemptive process schedulers.

  6. A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler.

    PubMed

    Butt, Muhammad Arif; Akram, Muhammad

    2016-01-01

    We present a new intuitionistic fuzzy rule-based decision-making system based on intuitionistic fuzzy sets for a process scheduler of a batch operating system. Our proposed intuitionistic fuzzy scheduling algorithm, inputs the nice value and burst time of all available processes in the ready queue, intuitionistically fuzzify the input values, triggers appropriate rules of our intuitionistic fuzzy inference engine and finally calculates the dynamic priority (dp) of all the processes in the ready queue. Once the dp of every process is calculated the ready queue is sorted in decreasing order of dp of every process. The process with maximum dp value is sent to the central processing unit for execution. Finally, we show complete working of our algorithm on two different data sets and give comparisons with some standard non-preemptive process schedulers. PMID:27652120

  7. A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing

    PubMed Central

    Lin, Ching-Miao; Lai, Feipei; Ho, Yi-Lwun; Hung, Chi-Sheng

    2015-01-01

    Background Telehealth care is a global trend affecting clinical practice around the world. To mitigate the workload of health professionals and provide ubiquitous health care, a comprehensive surveillance system with value-added services based on information technologies must be established. Objective We conducted this study to describe our proposed telesurveillance system designed for monitoring and classifying electrocardiogram (ECG) signals and to evaluate the performance of ECG classification. Methods We established a telesurveillance system with an automatic ECG interpretation mechanism. The system included: (1) automatic ECG signal transmission via telecommunication, (2) ECG signal processing, including noise elimination, peak estimation, and feature extraction, (3) automatic ECG interpretation based on the support vector machine (SVM) classifier and rule-based processing, and (4) display of ECG signals and their analyzed results. We analyzed 213,420 ECG signals that were diagnosed by cardiologists as the gold standard to verify the classification performance. Results In the clinical ECG database from the Telehealth Center of the National Taiwan University Hospital (NTUH), the experimental results showed that the ECG classifier yielded a specificity value of 96.66% for normal rhythm detection, a sensitivity value of 98.50% for disease recognition, and an accuracy value of 81.17% for noise detection. For the detection performance of specific diseases, the recognition model mainly generated sensitivity values of 92.70% for atrial fibrillation, 89.10% for pacemaker rhythm, 88.60% for atrial premature contraction, 72.98% for T-wave inversion, 62.21% for atrial flutter, and 62.57% for first-degree atrioventricular block. Conclusions Through connected telehealth care devices, the telesurveillance system, and the automatic ECG interpretation system, this mechanism was intentionally designed for continuous decision-making support and is reliable enough to reduce the

  8. Clinical decision support systems.

    PubMed

    Beeler, Patrick Emanuel; Bates, David Westfall; Hug, Balthasar Luzius

    2014-01-01

    Clinical decision support (CDS) systems link patient data with an electronic knowledge base in order to improve decision-making and computerised physician order entry (CPOE) is a requirement to set up electronic CDS. The medical informatics literature suggests categorising CDS tools into medication dosing support, order facilitators, point-of-care alerts and reminders, relevant information display, expert systems and workflow support. To date, CDS has particularly been recognised for improving processes. CDS successfully fostered prevention of deep-vein thrombosis, improved adherence to guidelines, increased the use of vaccinations, and decreased the rate of serious medication errors. However, CDS may introduce errors, and therefore the term "e-iatrogenesis" has been proposed to address unintended consequences. At least two studies reported severe treatment delays due to CPOE and CDS. In addition, the phenomenon of "alert fatigue" - arising from a high number of CDS alerts of low clinical significance - may facilitate overriding of potentially critical notifications. The implementation of CDS needs to be carefully planned, CDS interventions should be thoroughly examined in pilot wards only, and then stepwise introduced. A crucial feature of CPOE in combination with CDS is speed, since time consumption has been found to be a major factor determining failure. In the near future, the specificity of alerts will be improved, notifications will be prioritised and offer detailed advice, customisation of CDS will play an increasing role, and finally, CDS is heading for patient-centred decision support. The most important research question remains whether CDS is able to improve patient outcomes beyond processes.

  9. A rule-based approach for the correlation of alarms to support Disaster and Emergency Management

    NASA Astrophysics Data System (ADS)

    Gloria, M.; Minei, G.; Lersi, V.; Pasquariello, D.; Monti, C.; Saitto, A.

    2009-04-01

    application as CiscoWorks, HP OpenView NNM and Operation, BMC Patrol, etc. Analysis of text of an alarm can detect some keywords that allow to classify the particular event. The inference rules were developed by means an analysis about news regard real emergency found by web reaserches. We have seen that often a kind of emergency is characterized by more keyword. Keywords are not uniquely associated with a specific emergency, but they can be shared by different types of emergencies (such as. keyword "landslide" can be associated both emergency "landslide" and emergency "Flood"). However, the identification of two or more keywords associated with a particular type of emergency identified in most cases the correct type of emergency. So, for example, if text contains words as "water", "flood", "overflowing", "landslide" o other words belonging to the set of defined keywords or words that have some root of keywords, the system "decides" that this alarm belongs to specific typology, in this case "flood typology". The system has the memory of this information, so if a new alarm is reported and belongs to one of the typology already identified, it proceeds with the comparison of coordinates. The comparison between the centers of the alarms allows to see if they describe an area inscribed in an ideal circle that has centered on the first alarm and radius defined by the typology above mentioned. If this happens the system CI6 creates an emergency that has centered on the centre of that area and typology equal to that of the alarms. It follows that an emergency is represented by at least two alarms. Thus, the system suggests to manager (CI6's user) the possibility that most alarms can concern same events and makes a classification of this event. It is important to stress that CI6 is a system of decision support, hence also this service is limited to providing advice to the user to facilitate his task, leaving him the decision to accept it or not. REFERENCES SEC (Simple Event Correlator

  10. A Hybrid Approach Using Case-Based Reasoning and Rule-Based Reasoning to Support Cancer Diagnosis: A Pilot Study.

    PubMed

    Saraiva, Renata M; Bezerra, João; Perkusich, Mirko; Almeida, Hyggo; Siebra, Clauirton

    2015-01-01

    Recently there has been an increasing interest in applying information technology to support the diagnosis of diseases such as cancer. In this paper, we present a hybrid approach using case-based reasoning (CBR) and rule-based reasoning (RBR) to support cancer diagnosis. We used symptoms, signs, and personal information from patients as inputs to our model. To form specialized diagnoses, we used rules to define the input factors' importance according to the patient's characteristics. The model's output presents the probability of the patient having a type of cancer. To carry out this research, we had the approval of the ethics committee at Napoleão Laureano Hospital, in João Pessoa, Brazil. To define our model's cases, we collected real patient data at Napoleão Laureano Hospital. To define our model's rules and weights, we researched specialized literature and interviewed health professional. To validate our model, we used K-fold cross validation with the data collected at Napoleão Laureano Hospital. The results showed that our approach is an effective CBR system to diagnose cancer. PMID:26262174

  11. Taking a gamble or playing by the rules: Dissociable prefrontal systems implicated in probabilistic versus deterministic rule-based decisions

    PubMed Central

    Bhanji, Jamil P.; Beer, Jennifer S.; Bunge, Silvia A.

    2014-01-01

    A decision may be difficult because complex information processing is required to evaluate choices according to deterministic decision rules and/or because it is not certain which choice will lead to the best outcome in a probabilistic context. Factors that tax decision making such as decision rule complexity and low decision certainty should be disambiguated for a more complete understanding of the decision making process. Previous studies have examined the brain regions that are modulated by decision rule complexity or by decision certainty but have not examined these factors together in the context of a single task or study. In the present functional magnetic resonance imaging study, both decision rule complexity and decision certainty were varied in comparable decision tasks. Further, the level of certainty about which choice to make (choice certainty) was varied separately from certainty about the final outcome resulting from a choice (outcome certainty). Lateral prefrontal cortex, dorsal anterior cingulate cortex, and bilateral anterior insula were modulated by decision rule complexity. Anterior insula was engaged more strongly by low than high choice certainty decisions, whereas ventromedial prefrontal cortex showed the opposite pattern. These regions showed no effect of the independent manipulation of outcome certainty. The results disambiguate the influence of decision rule complexity, choice certainty, and outcome certainty on activity in diverse brain regions that have been implicated in decision making. Lateral prefrontal cortex plays a key role in implementing deterministic decision rules, ventromedial prefrontal cortex in probabilistic rules, and anterior insula in both. PMID:19781652

  12. Decision Support Systems in Libraries.

    ERIC Educational Resources Information Center

    Heindel, Allan; Napier, H. Albert

    Following a review of the contributions of computers and managerial science/operations research to the management of libraries, this paper introduces the concept of decision support systems. DSS, a blending of these techniques, can lead to more effective decisions by library managers. A case study of the utilization of a DSS in the budgeting…

  13. Decision Support Framework (DSF) (Formerly Decision Support Platform)

    EPA Science Inventory

    The Science Advisory Board (SAB) provided several comments on the draft Ecosystem Services Research Program's (ESRP's) Multi-Year Plan (MYP). This presentation provides a response to comments related to the decision support framework (DSF) part of Long-Term Goal 1. The comments...

  14. A shotgun wedding: business decision support meets clinical decision support.

    PubMed

    Oliveira, Jason

    2002-01-01

    By effectively closing the loop between the data, analytics, processes, and methods supporting business and clinical decision making, a healthcare organization closes the loop between its knowledge generation activities and its actions at the bedside: knowledge guiding actions, actions generating knowledge.

  15. Automating hypertext for decision support

    NASA Technical Reports Server (NTRS)

    Bieber, Michael

    1990-01-01

    A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.

  16. Strategic Decision Making and Group Decision Support Systems.

    ERIC Educational Resources Information Center

    McGrath, Michael Robert

    1986-01-01

    Institutional strategic decisions require the participation of every individual with a significant stake in the solution, and group decision support systems are being developed to respond to the political and consensual problems of collective decision-making. (MSE)

  17. EVALUATING ENVIRONMENTAL DECISION SUPPORT TOOLS.

    SciTech Connect

    SULLIVAN, T.

    2004-10-01

    Effective contaminated land management requires a number of decisions addressing a suite of technical, economic, and social concerns. These concerns include human health risks, ecological risks, economic costs, technical feasibility of proposed remedial actions, and the value society places on clean-up and re-use of formerly contaminated lands. Decision making, in the face of uncertainty and multiple and often conflicting objectives, is a vital and challenging role in environmental management that affects a significant economic activity. Although each environmental remediation problem is unique and requires a site-specific analysis, many of the key decisions are similar in structure. This has led many to attempt to develop standard approaches. As part of the standardization process, attempts have been made to codify specialist expertise into decision support tools. This activity is intended to facilitate reproducible and transparent decision making. The process of codifying procedures has also been found to be a useful activity for establishing and rationalizing management processes. This study will have two primary objectives. The first is to develop taxonomy for Decision Support Tools (DST) to provide a framework for understanding the different tools and what they are designed to address in the context of environmental remediation problems. The taxonomy will have a series of subject areas for the DST. From these subjects, a few key areas will be selected for further study and software in these areas will be identified. The second objective, will be to review the existing DST in the selected areas and develop a screening matrix for each software product.

  18. Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

    NASA Astrophysics Data System (ADS)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2013-04-01

    Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total

  19. Decision Technology Systems: A Vehicle to Consolidate Decision Making Support.

    ERIC Educational Resources Information Center

    Forgionne, Guisseppi A.

    1991-01-01

    Discussion of management decision making and the support needed to manage successfully highlights a Decision Technology System (DTS) that integrates other information systems. Topics discussed include computer information systems (CISs); knowledge gateways; the decision-making process; decision support systems (DSS); expert systems; and facility…

  20. Comparison of Support-Vector Machine and Sparse Representation Using a Modified Rule-Based Method for Automated Myocardial Ischemia Detection

    PubMed Central

    Tseng, Yi-Li; Lin, Keng-Sheng; Jaw, Fu-Shan

    2016-01-01

    An automatic method is presented for detecting myocardial ischemia, which can be considered as the early symptom of acute coronary events. Myocardial ischemia commonly manifests as ST- and T-wave changes on ECG signals. The methods in this study are proposed to detect abnormal ECG beats using knowledge-based features and classification methods. A novel classification method, sparse representation-based classification (SRC), is involved to improve the performance of the existing algorithms. A comparison was made between two classification methods, SRC and support-vector machine (SVM), using rule-based vectors as input feature space. The two methods are proposed with quantitative evaluation to validate their performances. The results of SRC method encompassed with rule-based features demonstrate higher sensitivity than that of SVM. However, the specificity and precision are a trade-off. Moreover, SRC method is less dependent on the selection of rule-based features and can achieve high performance using fewer features. The overall performances of the two methods proposed in this study are better than the previous methods. PMID:26925158

  1. Decision support for financial forecasting

    SciTech Connect

    Jairam, B.N.; Morris, J.D.; Emrich, M.L.; Hardee, H.K.

    1988-10-01

    A primary mission of the Budget Management Division of the Air Force is fiscal analysis. This involves formulating, justifying, and tracking financial data during budget preparation and execution. An essential requirement of this process is the ready availability and easy manipulation of past and current budget data. This necessitates the decentralization of the data. A prototypical system, BAFS (Budget Analysis and Forecasting System), that provides such a capability is presented. In its current state, the system is designed to be a decision support tool. A brief report of the budget decisions and activities is presented. The system structure and its major components are discussed. An insight into the implementation strategies and the tool used is provided. The paper concludes with a discussion of future enhancements and the system's evolution into an expert system. 4 refs., 3 figs.

  2. Decision Support Methods and Tools

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.; Alexandrov, Natalia M.; Brown, Sherilyn A.; Cerro, Jeffrey A.; Gumbert, Clyde r.; Sorokach, Michael R.; Burg, Cecile M.

    2006-01-01

    This paper is one of a set of papers, developed simultaneously and presented within a single conference session, that are intended to highlight systems analysis and design capabilities within the Systems Analysis and Concepts Directorate (SACD) of the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). This paper focuses on the specific capabilities of uncertainty/risk analysis, quantification, propagation, decomposition, and management, robust/reliability design methods, and extensions of these capabilities into decision analysis methods within SACD. These disciplines are discussed together herein under the name of Decision Support Methods and Tools. Several examples are discussed which highlight the application of these methods within current or recent aerospace research at the NASA LaRC. Where applicable, commercially available, or government developed software tools are also discussed

  3. Overview of environmental decision support software

    SciTech Connect

    Sullivan, T.M.; Moskowitz, P.D.; Gitten, M.

    1997-12-31

    Regulatory exposure limits form the basis for making decisions on the characterization, monitoring, and remediation of environmental contamination. This paper discusses the development of Decision Support Software (DSS) tools developed to support decisions pertaining to environmental management. Decision support software packages are computer-based programs that facilitate the use of data, models, and structured decision processes in decision making. They incorporate the information into an integrated package that presents results in a format useful for making environmental decisions. Six major analysis functions of DSS tools have been identified: site characterization, plume characterization, risk assessment including regulatory compliance assessment, remedy selection, remedy design optimization, and cost/benefit analysis. Decision support software is relatively new and is now beginning to see application in the field. This paper discusses existing DSS and the strengths and limitations of some of the DSS packages. General limitations of decision support software are also discussed.

  4. Decision support for clinical laboratory capacity planning.

    PubMed

    van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

    1995-01-01

    The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

  5. Decision Support Systems: The Need, The Challenge.

    ERIC Educational Resources Information Center

    Roberts, Michael M.

    1982-01-01

    The evolution of decision support systems (DSS) has enabled computer and information technology to assist the management process of decision making. Decision support systems are designed to look forward in time, to forecast outcomes of uncertain events. A 70-item bibliography is included. (MLW)

  6. Anatomy of a Decision Support System.

    ERIC Educational Resources Information Center

    Chachra, Vinod; Heterick, Robert C.

    1982-01-01

    The decision support system (DSS) environment, the functional requirements of a DSS, and the architectural requirements of the computer systems and communications network necessary to support a DSS are discussed. Changes in the computing environment that are necessary to implement decision support systems are suggested. (Author/MLW)

  7. Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care

    PubMed Central

    Sesen, M. Berkan; Peake, Michael D.; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael

    2014-01-01

    Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments. PMID:24990290

  8. Decision Support Systems for Academic Administration.

    ERIC Educational Resources Information Center

    Moore, Laurence J.; Greenwood, Allen G.

    1984-01-01

    The history and features of Decision Support Systems (DSS) and use of the approach by academic administrators are discussed. The objective of DSS is to involve the manager/decision maker in the decision-analysis process while simultaneously relieving that person of the burden of developing and performing detailed analysis. DSS represents a…

  9. Intelligent decision support in process environments

    SciTech Connect

    Hollnagel, E.; Mancini, G.; Woods, D.D.

    1986-01-01

    This book deals with the basis for design of intelligent systems to support human decision-making in supervisory control, and provides a view of how human and artificial cognitive systems can interact. It covers the design and development of intelligent decision aiding systems, as well as the testing and evaluation. Topics discussed include: decision theory; cognitive engineering; systems engineering; and artificial intelligence.

  10. Healthcare Decision Support System for Administration of Chronic Diseases

    PubMed Central

    Woo, Ji-In; Yang, Jung-Gi; Lee, Young-Ho

    2014-01-01

    Objectives A healthcare decision-making support model and rule management system is proposed based on a personalized rule-based intelligent concept, to effectively manage chronic diseases. Methods A Web service was built using a standard message transfer protocol for interoperability of personal health records among healthcare institutions. An intelligent decision service is provided that analyzes data using a service-oriented healthcare rule inference function and machine-learning platform; the rules are extensively compiled by physicians through a developmental user interface that enables knowledge base construction, modification, and integration. Further, screening results are visualized for the self-intuitive understanding of personal health status by patients. Results A recommendation message is output through the Web service by receiving patient information from the hospital information recording system and object attribute values as input factors. The proposed system can verify patient behavior by acting as an intellectualized backbone of chronic diseases management; further, it supports self-management and scheduling of screening. Conclusions Chronic patients can continuously receive active recommendations related to their healthcare through the rule management system, and they can model the system by acting as decision makers in diseases management; secondary diseases can be prevented and health management can be performed by reference to patient-specific lifestyle guidelines. PMID:25152830

  11. Exploiting multi-modal reasoning for knowledge management and decision support: an evaluation study.

    PubMed Central

    Montani, S.; Bellazzi, R.

    2000-01-01

    We present the first evaluation results of a knowledge management and decision support system for Type I diabetes patients' care. Such system, meant to help physicians in therapy revision, relies on the integration of Rule Based Reasoning and Case Based Reasoning, and exploits both explicit and implicit knowledge. Reliability was positively judged by a group of expert diabetologists; an increase in its performances is foreseen as new knowledge will be acquired, through the system usage in clinical practice. PMID:11079951

  12. Using Visualization in Cockpit Decision Support Systems

    SciTech Connect

    Aragon, Cecilia R.

    2005-07-01

    In order to safely operate their aircraft, pilots must makerapid decisions based on integrating and processing large amounts ofheterogeneous information. Visual displays are often the most efficientmethod of presenting safety-critical data to pilots in real time.However, care must be taken to ensure the pilot is provided with theappropriate amount of information to make effective decisions and notbecome cognitively overloaded. The results of two usability studies of aprototype airflow hazard visualization cockpit decision support systemare summarized. The studies demonstrate that such a system significantlyimproves the performance of helicopter pilots landing under turbulentconditions. Based on these results, design principles and implicationsfor cockpit decision support systems using visualization arepresented.

  13. Isabel, a clinical decision support system.

    PubMed

    Vardell, Emily; Moore, Mary

    2011-01-01

    A clinical decision support system (CDSS) is an interactive tool designed to assist clinicians in making decisions, such as determining a diagnosis. The Isabel Database is a CDSS featuring a clinical checklist and topic-specific knowledge components. This column contains an overview of the database, provides searching tips, and places Isabel within the context of the CDSS field. PMID:21534115

  14. A Hyperknowledge Framework of Decision Support Systems.

    ERIC Educational Resources Information Center

    Chang, Ai-Mei; And Others

    1994-01-01

    Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…

  15. Geospatial decision support systems for societal decision making

    USGS Publications Warehouse

    Bernknopf, R.L.

    2005-01-01

    While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the

  16. A Decision Support System for Supervised Assignment in Banking Decisions

    NASA Astrophysics Data System (ADS)

    Rigopoulos, George; Psarras, John; Askounis, Dimitrios Th.

    This study presents a Decision Support System (DSS) which supports assignment of actions (e.g., numbers, projects, people etc.) into predefined categories according to their score on evaluation criteria. It implements a novel classification algorithm based on multicriteria analysis and fuzzy preference relations. More detailed, assignment to classes is based on the concept of category threshold, which defines at what degree an alternative can be included in a specific category. For each category a threshold is defined by the corresponding decision maker, which indicates its lower limit with respect to the evaluation criteria. Actions are then evaluated according to the criteria and fuzzy inclusion degrees are calculated for each category. Finally, an action is assigned to the category for which the inclusion degree is the maximum. The DSS implements the above classification algorithm, providing a user-friendly interface, which supports decision makers to formulate and solve similar problems. In addition to the DSS, we present a real world application at a classification problem within the environment of a Greek bank. Results derived from evaluation experiments in the business environment provide evidence that the proposed methodology and the DSS can effectively support decision makers in classification decisions. The methodology as well as the proposed DSS can be used to classification problems not only in financial domain but to a variety of domains such as production, environmental, or human resources.

  17. Group decision support using Toulmin argument structures

    SciTech Connect

    Janssen, T. |; Sage, A.P.

    1996-12-31

    This paper addresses the need for sound science, technology, and management assessment relative to environmental policy decision making through an approach that involves a logical structure for evidence, a framed decision-making process, and an environment that encourages group participation. Toulmin-based logic possesses these characteristics and is used as the basis for development of a group decision support system. This system can support several user groups, such as pesticide policy-making experts, who can use the support system to state arguments for or against an important policy issue, and pest management experts, who can use the system to assist in identifying and evaluating alternatives for controlling pests on agricultural commodities. The resulting decision support system assists in improving the clarity of the lines of reasoning used in specific situations; the warrants, grounds, and backings that are used to support claims and specific lines of reasoning; and the contradictions, rebuttals, and arguments surrounding each step in the reasoning process associated with evaluating a claim or counterclaim. Experts and decisions makers with differing views can better understand each other`s thought processes. The net effect is enhanced communications and understanding of the whole picture and, in many cases, consensus on decisions to be taken.

  18. Using Visualization in Cockpit Decision Support Systems

    NASA Technical Reports Server (NTRS)

    Aragon, Cecilia R.

    2005-01-01

    In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

  19. Bayesian Decision Support for Adaptive Lung Treatments

    NASA Astrophysics Data System (ADS)

    McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

    2014-03-01

    Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

  20. Computerized Clinical Decision Support: Contributions from 2014

    PubMed Central

    Koutkias, V.

    2015-01-01

    Summary Objective To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term. PMID:26293858

  1. Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System

    PubMed Central

    Bal, Mert; Amasyali, M. Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

    2014-01-01

    The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets. PMID:25295291

  2. Adaptive Rule Based Fetal QRS Complex Detection Using Hilbert Transform

    PubMed Central

    Ulusar, Umit D.; Govindan, R.B.; Wilson, James D.; Lowery, Curtis L.; Preissl, Hubert; Eswaran, Hari

    2010-01-01

    In this paper we introduce an adaptive rule based QRS detection algorithm using the Hilbert transform (adHQRS) for fetal magnetocardiography processing. Hilbert transform is used to combine multiple channel measurements and the adaptive rule based decision process is used to eliminate spurious beats. The algorithm has been tested with a large number of datasets and promising results were obtained. PMID:19964648

  3. Decision Support and Knowledge-Based Systems.

    ERIC Educational Resources Information Center

    Konsynski, Benn R.; And Others

    1988-01-01

    A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…

  4. Modeling uncertainty in requirements engineering decision support

    NASA Technical Reports Server (NTRS)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  5. Decision support system for nursing management control

    SciTech Connect

    Ernst, C.J.

    1983-01-01

    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.

  6. Decision Support Systems in Academic Administration.

    ERIC Educational Resources Information Center

    Turban, Efraim; And Others

    1988-01-01

    Presents an overview of a computerized Decision Support System (DSS) for academic administrators. Following a discussion of its capabilities, the various components of a DSS are examined as well as the development tools needed. Examples follow of DSS in two universities, and various development and implementation issues are considered. (TE)

  7. Transferring Decision Support Concepts to Evaluation.

    ERIC Educational Resources Information Center

    Sauter, Vicki L.; Mandell, Marvin B.

    1990-01-01

    Use of decision support systems (DSS) to increase the utilization of management science models and accounting information is discussed. It is argued that application of the conceptual foundations of DSS to evaluation and other forms of applied social research is an effective means of increasing evaluation utilization by policymakers. (TJH)

  8. A Multiple Objective Decision Support Tool (MODS)

    2003-12-14

    The Multiple Objective Decision Support (MODS) tool is an automated tool used to assist decision makers and policy analysts with multiple-objective decision problems. The classes of problems that this decision support tool addresses have both multiple objectives and multiple stakeholders. Decision problems, which have multiple objectives that in general cannot be maximized simultaneously, and multiple stakeholders, who have different perspectives about the relative importance of the objectives, require analytic approaches and tools that can providemore » flexible support to decision makers. This tool provides capabilities for the management, analysis, and graphical display for these types of decision problems drawn from diverse problem domains. The MODS tool is a unique integration of analysis algorithms, an information database, and a graphical user interface. This collection of algorithms, the combination of an information database with the analysis into a single tool, and the graphical user interface provides a technically advanced tool to decision makers and policy analysts. There are two main issues when addressing problems of this type: what set of attributes should be used to characterize the tokens in the domain of interest, and how should the values of these attributes and their weights be determined and combined to provide a relative ordering to the tokens. This tool addresses both of these issues. This decision support tool provides a flexible way to derive and use a chosen set of attributes. For example, the tool could be used to first perform a paired comparison of a large set of attributes and from this evaluation select those attributes that have the highest weights. The flexibility of the tool allows experimentation with various attribute sets and this capability, along with domain expertise, addresses the first issue. To address the second issue, several algorithms have been implemented. For example, two algorithms that have been implemented are

  9. The conceptual foundation of environmental decision support.

    PubMed

    Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

    2015-05-01

    Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization. PMID:25748599

  10. The conceptual foundation of environmental decision support.

    PubMed

    Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

    2015-05-01

    Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization.

  11. Decision support for patient care: implementing cybernetics.

    PubMed

    Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A

    2004-01-01

    The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.

  12. Decision support tools for policy and planning

    SciTech Connect

    Jacyk, P.; Schultz, D.; Spangenberg, L.

    1995-07-01

    A decision support system (DSS) is being developed at the Radioactive Liquid Waste Treatment Facility, Los Alamos National Laboratory (LANL). The DSS will be used to evaluate alternatives for improving LANL`s existing central radioactive waste water treatment plant and to evaluate new site-wide liquid waste treatment schemes that are required in order to handle the diverse waste streams produced at LANL. The decision support system consists of interacting modules that perform the following tasks: rigorous process simulation, configuration management, performance analysis, cost analysis, risk analysis, environmental impact assessment, transportation modeling, and local, state, and federal regulation compliance checking. Uncertainty handling techniques are used with these modules and also with a decision synthesis module which combines results from the modules listed above. We believe the DSS being developed can be applied to almost any other industrial water treatment facility with little modification because in most situations the waste streams are less complex, fewer regulations apply, and the political environment is simpler. The techniques being developed are also generally applicable to policy and planning decision support systems in the chemical process industry.

  13. Decision Support for Operations and Maintenance IV

    SciTech Connect

    2011-12-22

    DSOM (Decision Support for Operations and Maintenance) is an expert operations and maintenance system that integrates plant operations, fuel management, and maintenance processes. The DSOM package provides operators with the information they need for cost-effective operating decisions creating savings in fuel, personnel, maintenance, and plant life extension. DSOM provides operators real-time system performance information to allow them to determine if the plant is malfunctioning or running below expectations. By catching potential problems, DSOM enables plants to operate safely at peak efficiency, while providing a higher level of reliability and safety.

  14. Decision Support for Operations and Maintenance IV

    2011-12-22

    DSOM (Decision Support for Operations and Maintenance) is an expert operations and maintenance system that integrates plant operations, fuel management, and maintenance processes. The DSOM package provides operators with the information they need for cost-effective operating decisions creating savings in fuel, personnel, maintenance, and plant life extension. DSOM provides operators real-time system performance information to allow them to determine if the plant is malfunctioning or running below expectations. By catching potential problems, DSOM enables plantsmore » to operate safely at peak efficiency, while providing a higher level of reliability and safety.« less

  15. From hydrological modelling to decision support

    NASA Astrophysics Data System (ADS)

    Haberlandt, U.

    2010-08-01

    Decision support for planning and management of water resources needs to consider many target criteria simultaneously like water availability, water quality, flood protection, agriculture, ecology, etc. Hydrologic models provide information about the water balance components and are fundamental for the simulation of ecological processes. Objective of this contribution is to discuss the suitability of classical hydrologic models on one hand and of complex eco-hydrologic models on the other hand to be used as part of decision support systems. The discussion is based on results from two model comparison studies. It becomes clear that none of the hydrologic models tested fulfils all requirements in an optimal sense. Regarding the simulation of water quality parameters like nitrogen leaching a high uncertainty needs to be considered. Recommended for decision support is a hybrid metamodel approach, which comprises a hydrologic model, empirical relationships for the less dynamic processes and makes use of simulation results from complex eco-hydrologic models through second-order modelling at a generalized level.

  16. Decision support system for drinking water management

    NASA Astrophysics Data System (ADS)

    Janža, M.

    2012-04-01

    The problems in drinking water management are complex and often solutions must be reached under strict time constrains. This is especially distinct in case of environmental accidents in the catchment areas of the wells that are used for drinking water supply. The beneficial tools that can help decision makers and make program of activities more efficient are decision support systems (DSS). In general they are defined as computer-based support systems that help decision makers utilize data and models to solve unstructured problems. The presented DSS was developed in the frame of INCOME project which is focused on the long-term stable and safe drinking water supply in Ljubljana. The two main water resources Ljubljana polje and Barje alluvial aquifers are characterized by a strong interconnection of surface and groundwater, high vulnerability, high velocities of groundwater flow and pollutant transport. In case of sudden pollution, reactions should be very fast to avoid serious impact to the water supply. In the area high pressures arising from urbanization, industry, traffic, agriculture and old environmental burdens. The aim of the developed DSS is to optimize the activities in cases of emergency water management and to optimize the administrative work regarding the activities that can improve groundwater quality status. The DSS is an interactive computer system that utilizes data base, hydrological modelling, and experts' and stakeholders' knowledge. It consists of three components, tackling the different abovementioned issues in water management. The first one utilizes the work on identification, cleaning up and restoration of illegal dumpsites that are a serious threat to the qualitative status of groundwater. The other two components utilize the predictive capability of the hydrological model and scenario analysis. The user interacts with the system by a graphical interface that guides the user step-by-step to the recommended remedial measures. Consequently, the

  17. Web Support System for Group Collaborative Decisions

    NASA Astrophysics Data System (ADS)

    Rigopoulos, George; Psarras, John; Askounis, Dimitrios Th.

    In this research, we present a Group Decision Support System (GDSS) based on web technology, which can be used in asynchronous mode from group members. It supports small collaborative groups in classification decisions, implementing a supervised multicriteria methodology. A facilitator, who defines necessary parameters and initiates the procedure, coordinates the entire operation. Next, members evaluate the proposed parameter set and express their preferences in numeric format. Aggregation of individuals` preferences is executed at the parameter level by utilization of OWA operator and a group parameter set is produced which is used as input for the classification algorithm. A multicriteria classification algorithm is used for the classification of actions (people, projects etc.). Finally, group members evaluate results and consensus as well as satisfaction indexes are calculated. In case of low acceptance level, parameters are redefined and aggregation phase is repeated. The system has been utilized effectively to solve group classification problems in business environment. The overall architecture as well the methodology is presented, along with a sample application. Empirical findings from GDSS application and the methodology provide evidence that it is a valid approach for similar decision problems in numerous business environments, including production, human resources and operations.

  18. Constructing Clinical Decision Support Systems for Adverse Drug Event Prevention: A Knowledge-based Approach.

    PubMed

    Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Collyda, Chrysa; Chazard, Emmanuel; McNair, Peter; Beuscart, Regis; Maglaveras, Nicos

    2010-11-13

    A knowledge-based approach is proposed that is employed for the construction of a framework suitable for the management and effective use of knowledge on Adverse Drug Event (ADE) prevention. The framework has as its core part a Knowledge Base (KB) comprised of rule-based knowledge sources, that is accompanied by the necessary inference and query mechanisms to provide healthcare professionals and patients with decision support services in clinical practice, in terms of alerts and recommendations on preventable ADEs. The relevant Knowledge Based System (KBS) is developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the foundations of the framework, its knowledge model and KB structure, as well as recent progress as regards the population of the KB, the implementation of the KBS, and results on the KBS verification in decision support operation.

  19. IPDS: Integrated Planning Decision Support System

    SciTech Connect

    Mejia-Navarro, M.; Garcia, L.A.

    1995-12-31

    The Integrated Planning Decision Support System (IPDS) is designed as a decision support system (DSS) to assist governments and communities in evaluation of geological hazards, vulnerability, and risk. The IPDS system incorporates the Geographic Information Systems (GIS) Geographic Resource Analysis Support System (GRASS) and engineering numerical models within a Graphic User Interface (GUI), to provide the user with comprehensive modelling capabilities for geological hazards, vulnerability, and risk assessment. The methodology that IPDS follows for the evaluation of hazards takes into account the weight of each influencing factor within hazardous geologic processes. IPDS interactive algorithms compute the following parameters for each cell (based on the maximum resolution of the data): the related hazard, the vulnerability to geological hazards, and the risk. IPDS is designed to assess any generic hazard, such as debris flows, subsidence, and floods, with probable maximum precipitation and seismicity as triggering factors for susceptibility scenarios. The regular items considered in vulnerability analysis are (1) ecosystem sensitivity, (2) economic vulnerability, and (3) social infrastructure vulnerability. The risk is assessed as a function of hazard and vulnerability.

  20. Computational Support for Technology- Investment Decisions

    NASA Technical Reports Server (NTRS)

    Adumitroaie, Virgil; Hua, Hook; Lincoln, William; Block, Gary; Mrozinski, Joseph; Shelton, Kacie; Weisbin, Charles; Elfes, Alberto; Smith, Jeffrey

    2007-01-01

    Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.

  1. Sediment Analysis Network for Decision Support (SANDS)

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.

    2009-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms

  2. Flood Impact Modelling to support decision making

    NASA Astrophysics Data System (ADS)

    Owen, Gareth; Quinn, Paul; O'Donnell, Greg

    2015-04-01

    Much of what is known about the impacts of landuse change and Natural Flood Management (NFM) is at the local/plot scale. Evidence of the downstream impacts at the larger catchment scale is limited. However, the strategic and financial decisions of land managers, stakeholders and policy makers are made at the larger scale. There are a number of techniques that have the potential to scale local impacts to the catchment scale. This poster will show findings for the 30km2 Leven catchment, North Yorkshire, England. A NFM approach has been adopted by the Environment Agency to reduce flood risk within the catchment. A dense network of stream level gauges were installed in the catchment at the commencement of this project to gain a detailed understanding of the catchment behaviour during storm events. A novel Flood Impact Modelling (FIM) approach has been adopted which uses the network of gauges to disaggregate the outlet hydrograph in terms of source locations. Using a combination of expert opinion and local evidence, the model can be used to assess the impacts of distributed changes in land use management and NFM on flood events. A number of potential future landuse and NFM scenarios have been modelled to investigate their impact on flood peaks. These modelled outcomes are mapped to a simple Decision Support Matrix (DSM). The DSM encourages end users (e.g. land managers and policy makers) to develop an NFM scheme by studying the degree to which local runoff can be attenuated and how that flow will propagate through the network to the point of impact. The DSM relates the impact on flood peaks in terms of alterations to soil management practices and landscape flow connectivity (e.g. soil underdrainage), which can be easily understood by farmers and land managers. The DSM and the FIM together provide a simple to use and transparent modelling tool, making best use of expert knowledge, to support decision making.

  3. A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-01-01

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  4. A Semantic Approach with Decision Support for Safety Service in Smart Home Management

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-01-01

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

  5. A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-01-01

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

  6. Rule-based simulation models

    NASA Technical Reports Server (NTRS)

    Nieten, Joseph L.; Seraphine, Kathleen M.

    1991-01-01

    Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

  7. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-01-01

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks. PMID:26610496

  8. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-01-01

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks. PMID:26610496

  9. 12 CFR 1290.4 - Decision on community support statements.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 12 Banks and Banking 7 2011-01-01 2011-01-01 false Decision on community support statements. 1290... COMMUNITY SUPPORT REQUIREMENTS § 1290.4 Decision on community support statements. (a) Action on community support statements. FHFA will act on each community support statement in accordance with the...

  10. Decision Support for Emergency Operations Centers

    NASA Technical Reports Server (NTRS)

    Harvey, Craig; Lawhead, Joel; Watts, Zack

    2005-01-01

    The Flood Disaster Mitigation Decision Support System (DSS) is a computerized information system that allows regional emergency-operations government officials to make decisions regarding the dispatch of resources in response to flooding. The DSS implements a real-time model of inundation utilizing recently acquired lidar elevation data as well as real-time data from flood gauges, and other instruments within and upstream of an area that is or could become flooded. The DSS information is updated as new data become available. The model generates realtime maps of flooded areas and predicts flood crests at specified locations. The inundation maps are overlaid with information on population densities, property values, hazardous materials, evacuation routes, official contact information, and other information needed for emergency response. The program maintains a database and a Web portal through which real-time data from instrumentation are gathered into the database. Also included in the database is a geographic information system, from which the program obtains the overlay data for areas of interest as needed. The portal makes some portions of the database accessible to the public. Access to other portions of the database is restricted to government officials according to various levels of authorization. The Flood Disaster Mitigation DSS has been integrated into a larger DSS named REACT (Real-time Emergency Action Coordination Tool), which also provides emergency operations managers with data for any type of impact area such as floods, fires, bomb

  11. Semantic technologies in a decision support system

    NASA Astrophysics Data System (ADS)

    Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

    2015-10-01

    The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

  12. Computerised clinical decision support for suspected PE.

    PubMed

    Jiménez, David; Resano, Santiago; Otero, Remedios; Jurkojc, Carolina; Portillo, Ana Karina; Ruiz-Artacho, Pedro; Corres, Jesús; Vicente, Agustina; den Exter, Paul L; Huisman, Menno V; Moores, Lisa; Yusen, Roger D

    2015-09-01

    This study aimed to determine the effect of an evidence-based clinical decision support (CDS) algorithm on the use and yield of CT pulmonary angiography (CTPA) and on outcomes of patients evaluated in the emergency department (ED) for suspected PE. The study included 1363 consecutive patients evaluated for suspected PE in an ED during 12 months before and 12 months after initiation of CDS use. Introduction of CDS was associated with decreased CTPA use (55% vs 49%; absolute difference (AD), 6.3%; 95% CI 1.0% to 11.6%; p=0.02). The use of CDS was associated with fewer symptomatic venous thromboembolic events during follow-up in patients with an initial negative diagnostic evaluation for PE (0.7% vs 3.2%; AD 2.5%; 95% CI 0.9% to 4.6%; p<0.01).

  13. The ECG as decision support in STEMI.

    PubMed

    Ripa, Maria Sejersten

    2012-03-01

    The electrocardiogram (ECG) can be used for determining the presence, location and extent of jeopardized myocardium during acute coronary occlusion. Accordingly, the ECG has become essential in the treatment of patients with acute coronary syndrome (ACS). This thesis aims at optimizing the decision support, provided by the ECG, for choosing the best treatment strategy in the individual patient with ST-segment elevation acute myocardial infarction (STEMI). ECG recorded in the prehospital setting has become the standard of care in many communities, but to achieve the full advantage of this early approach it is important that the ECG is recorded from accurately placed electrodes to produce an ECG that resembles the standard 12-lead ECG. Accurate electrode placement is difficult especially in the acute setting, and we investigated an alternative lead system with fewer electrodes in easily identified positions. We showed that the system produced waveforms similar to the standard 12-lead ECG. However, occasional diagnostic errors were seen, compromising general acceptance of the system. Once the ECG has been recorded a decision regarding triage must be made on the basis of a correct ECG diagnosis. We found that trained paramedics can diagnose STEMI correctly in patients without ECG confounding factors, while the presence of ECG confounding factors decreased their ability substantially. Consequently, since many patients do present with ECG confounding factors, transmission to an on-call cardiologist for an early correct diagnosis is needed. We showed that time to pPCI was reduced by more than 1 hour by transmitting prehospital ECG to a cardiologist's handheld device for diagnosis, triage, and activation of the catheterization laboratory when needed. The optimal treatment strategy is dependent on the duration of ischemia however patient information is often inaccurate. Accordingly, it would be advantageous if the first available ECG can help identify patients who will

  14. Quantitative Decision Support Requires Quantitative User Guidance

    NASA Astrophysics Data System (ADS)

    Smith, L. A.

    2009-12-01

    Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output

  15. User Centered Clinical Decision Support Tools

    PubMed Central

    Sofianou, A.; Kannry, J.; Mann, D.M.; McGinn, T.G.

    2014-01-01

    Summary Background Dissemination and adoption of clinical decision support (CDS) tools is a major initiative of the Affordable Care Act’s Meaningful Use program. Adoption of CDS tools is multipronged with personal, organizational, and clinical settings factoring into the successful utilization rates. Specifically, the diffusion of innovation theory implies that ‘early adopters’ are more inclined to use CDS tools and younger physicians tend to be ranked in this category. Objective This study examined the differences in adoption of CDS tools across providers’ training level. Participants From November 2010 to 2011, 168 residents and attendings from an academic medical institution were enrolled into a randomized controlled trial. Intervention The intervention arm had access to the CDS tool through the electronic health record (EHR) system during strep and pneumonia patient visits. Main Measures The EHR system recorded details on how intervention arm interacted with the CDS tool including acceptance of the initial CDS alert, completion of risk-score calculators and the signing of medication order sets. Using the EHR data, the study performed bivariate tests and general estimating equation (GEE) modeling to examine the differences in adoption of the CDS tool across residents and attendings. Key Results The completion rates of the CDS calculator and medication order sets were higher amongst first year residents compared to all other training levels. Attendings were the less likely to accept the initial step of the CDS tool (29.3%) or complete the medication order sets (22.4%) that guided their prescription decisions, resulting in attendings ordering more antibiotics (37.1%) during an CDS encounter compared to residents. Conclusion There is variation in adoption of CDS tools across training levels. Attendings tended to accept the tool less but ordered more medications. CDS tools should be tailored to clinicians’ training levels. PMID:25589914

  16. 12 CFR 944.4 - Decision on community support statements.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Decision on community support statements. 944.4 Section 944.4 Banks and Banking FEDERAL HOUSING FINANCE BOARD FEDERAL HOME LOAN BANK MISSION COMMUNITY SUPPORT REQUIREMENTS § 944.4 Decision on community support statements. (a) Action on community...

  17. Rule-Based Runtime Verification

    NASA Technical Reports Server (NTRS)

    Barringer, Howard; Goldberg, Allen; Havelund, Klaus; Sen, Koushik

    2003-01-01

    We present a rule-based framework for defining and implementing finite trace monitoring logics, including future and past time temporal logic, extended regular expressions, real-time logics, interval logics, forms of quantified temporal logics, and so on. Our logic, EAGLE, is implemented as a Java library and involves novel techniques for rule definition, manipulation and execution. Monitoring is done on a state-by-state basis, without storing the execution trace.

  18. Case-based reasoning in Intelligent Health Decision Support Systems.

    PubMed

    González, Carolina; López, Diego M; Blobel, Bernd

    2013-01-01

    Decision-making is a crucial task for decision makers in healthcare, especially because decisions have to be made quickly, accurately and under uncertainty. Taking into account the importance of providing quality decisions, offering assistance in this complex process has been one of the main challenges of Artificial Intelligence throughout history. Decision Support Systems (DSS) have gained popularity in the medical field for their efficacy to assist decision-making. In this sense, many DSS have been developed, but only few of them consider processing and analysis of information contained in electronic health records, in order to identify individual or population health risk factors. This paper deals with Intelligent Decision Support Systems that are integrated into Electronic Health Records Systems (EHRS) or Public Health Information Systems (PHIS). It provides comprehensive support for a wide range of decisions with the purpose of improving quality of care delivered to patients or public health planning, respectively.

  19. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS

    EPA Science Inventory

    Decision makers using environmental decision support tools are often confronted with information that predicts a multitude of different human health effects due to environmental stressors. If these health effects need to be contrasted with costs or compared with alternative scena...

  20. From Prediction to Prescription: Intelligent Decision Support for Variable Rate Fertilization

    SciTech Connect

    Fink, Raymond Keith; Hoskinson, Reed Louis; Hess, John Richard

    2001-07-01

    We describe the use of machine learning methods in the analysis of spatial soil fertility, soil physical characteristics, and yield data, with a particular objective of determining local (field- to farm-scale) crop response patterns. For effective prescriptive use, the output of these tools is augmented with economic data and operational constraints, and recast as a rulebased decision support tool to maximize economic return in variable rate fertilization systems. We describe some of the practical issues addressed in development of one such system, including data preparation, adaptation of regression tree output for use in a rule-based expert system, and incorporation of real-world limits on system recommendations. Results from various field trials of this system are summarized.

  1. Reef Ecosystem Services and Decision Support Database

    EPA Science Inventory

    This scientific and management information database utilizes systems thinking to describe the linkages between decisions, human activities, and provisioning of reef ecosystem goods and services. This database provides: (1) Hierarchy of related topics - Click on topics to navigat...

  2. A conceptual evolutionary aseismic decision support framework for hospitals

    NASA Astrophysics Data System (ADS)

    Hu, Yufeng; Dargush, Gary F.; Shao, Xiaoyun

    2012-12-01

    In this paper, aconceptual evolutionary framework for aseismic decision support for hospitalsthat attempts to integrate a range of engineering and sociotechnical models is presented. Genetic algorithms are applied to find the optimal decision sets. A case study is completed to demonstrate how the frameworkmay applytoa specific hospital.The simulations show that the proposed evolutionary decision support framework is able to discover robust policy sets in either uncertain or fixed environments. The framework also qualitatively identifies some of the characteristicbehavior of the critical care organization. Thus, by utilizing the proposedframework, the decision makers are able to make more informed decisions, especially toenhance the seismic safety of the hospitals.

  3. Future of electronic health records: implications for decision support.

    PubMed

    Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

    2012-01-01

    The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data

  4. The design of aircraft using the decision support problem technique

    NASA Technical Reports Server (NTRS)

    Mistree, Farrokh; Marinopoulos, Stergios; Jackson, David M.; Shupe, Jon A.

    1988-01-01

    The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems.

  5. Automation and Accountability in Decision Support System Interface Design

    ERIC Educational Resources Information Center

    Cummings, Mary L.

    2006-01-01

    When the human element is introduced into decision support system design, entirely new layers of social and ethical issues emerge but are not always recognized as such. This paper discusses those ethical and social impact issues specific to decision support systems and highlights areas that interface designers should consider during design with an…

  6. Development of Asset Management Decision Support Tools for Power Equipment

    NASA Astrophysics Data System (ADS)

    Okamoto, Tatsuki; Takahashi, Tsuguhiro

    Development of asset management decision support tools become very intensive in order to reduce maintenance cost of power equipment due to the liberalization of power business. This article reviews some aspects of present status of asset management decision support tools development for power equipment based on the papers published in international conferences, domestic conventions, and several journals.

  7. Decision Support Systems in Elementary and Secondary Educational Administration.

    ERIC Educational Resources Information Center

    Fisher, Janet Cameron; And Others

    1990-01-01

    A decision support system (DSS) is an interactive computerized system capable of providing direct, personal support for complex managerial decisions. This paper reviews DDSs and their general capabilities, describes potential benefits to school administrators, presents DDS applications in several school districts, and discusses implementation…

  8. Environmental Decision Support with Consistent Metrics

    EPA Science Inventory

    One of the most effective ways to pursue environmental progress is through the use of consistent metrics within a decision making framework. The US Environmental Protection Agency’s Sustainable Technology Division has developed TRACI, the Tool for the Reduction and Assessment of...

  9. Supporting Medical Decision Making with Argumentation Tools

    ERIC Educational Resources Information Center

    Lu, Jingyan; Lajoie, Susanne P.

    2008-01-01

    This study investigated the collaborative decision-making and communicative discourse of groups of learners engaged in a simulated medical emergency in two conditions. In one condition subgroups used a traditional whiteboard (TW group) to document medical arguments on how to solve a medical emergency. In the other condition subgroups used…

  10. Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

    ERIC Educational Resources Information Center

    Erskine, Michael A.

    2013-01-01

    As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

  11. The Contribution of a Decision Support System to Educational Decision-Making Processes

    ERIC Educational Resources Information Center

    Klein, Joseph; Ronen, Herman

    2003-01-01

    In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…

  12. Group Decision Support Systems and Group Communication: A Comparison of Decision Making in Computer-Supported and Nonsupported Groups.

    ERIC Educational Resources Information Center

    Poole, Marshall Scott; And Others

    1993-01-01

    Explores the effects of Group Decision Support Systems (GDSS) on small group communication and decision-making processes. Finds that comparing GDSS, manual, and baseline conditions enables separation of effects resulting from procedural structures from those resulting from computerization. Results support some aspects of the research model and…

  13. [A decision-support system for hematology].

    PubMed

    Straka, L; Stránský, P; Kmonícek, M

    1998-01-01

    Thrombocytopenia and following bleeding at the treatment of hematological malignancies is a dangerous complication. The indication of thrombocyte transfusion is the key point for the therapy and proylaxy of bleeding. The all problem is divided into two parts. Evaluation of the risk of bleeding (80% of decision), estimation of the risk of aloimunization and risk of connected with the transfusion (20% decision). For now we are concentrated to the evaluation of the risk of bleeding. In the first stage we are concentrated to statistical evaluation of values to define factors possibly highering the risk of bleeding. Factors were determined with help of two test, GUHA method and using literature. For recognized factors were trained 3 layer neuron nets with a non-linear method pack propagation. After that an application was developed to determine the risk of bleeding for a routine use in clinical practice.

  14. New approaches for real time decision support systems

    NASA Technical Reports Server (NTRS)

    Hair, D. Charles; Pickslay, Kent

    1994-01-01

    NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

  15. Decision support systems for robotic surgery and acute care

    NASA Astrophysics Data System (ADS)

    Kazanzides, Peter

    2012-06-01

    Doctors must frequently make decisions during medical treatment, whether in an acute care facility, such as an Intensive Care Unit (ICU), or in an operating room. These decisions rely on a various information sources, such as the patient's medical history, preoperative images, and general medical knowledge. Decision support systems can assist by facilitating access to this information when and where it is needed. This paper presents some research eorts that address the integration of information with clinical practice. The example systems include a clinical decision support system (CDSS) for pediatric traumatic brain injury, an augmented reality head- mounted display for neurosurgery, and an augmented reality telerobotic system for minimally-invasive surgery. While these are dierent systems and applications, they share the common theme of providing information to support clinical decisions and actions, whether the actions are performed with the surgeon's own hands or with robotic assistance.

  16. Decision Support Framework (DSF) Team Research Implementation Plan

    EPA Science Inventory

    The mission of ORD's Ecosystem Services Research Program (ESRP) is to provide the information and methods needed by decision-makers to assess the benefits of ecosystem goods and services to human well-being for inclusion in management alternatives. The Decision Support Framework...

  17. Computer-Based Support of Organizational Decision Making.

    ERIC Educational Resources Information Center

    Bonczek, Robert H.; And Others

    1979-01-01

    Explores the extent to which computer facilities can be used to support organizational decision-making processes beyond mere performance of information retrieval. Human perceptual and judgmental processes, as they apply to organizational decisions, are examined as a basis for the design of a generalized, intelligent problem processor. (Author/RAO)

  18. The Future of Decision Support Systems in Institutional Research.

    ERIC Educational Resources Information Center

    Rohrbaugh, John

    1986-01-01

    In the context of decision support systems (DSS) use, four perspectives on evaluating decisions (consensual, political, empirical, and rational) and four models of organizational effectiveness (human relations, open system, internal process, and rational goal) are examined for their implications for DSS implementation and evaluation. (MSE)

  19. Decision Support Systems: An Introduction for Program Evaluators.

    ERIC Educational Resources Information Center

    O'Sullivan, Elizabethann

    1985-01-01

    Decision Support Systems (DSS) are automated information systems designed to aid administrative decision making. A literature review on the design, implementation, and evaluation of DSS, suggests that evaluators act as liasons between designers and managers, identify and collect data for DSS, and evaluate DSS. (Author/EGS)

  20. A decision class analysis of critical care life-support decision-making.

    PubMed

    Seiver, A

    1993-02-01

    Decision analysis is a powerful methodology that can help clinicians make good decisions. Because it is not practical to place a decision analyst at the bedside in critical care units, the application of this methodology will require leveraging the analyst through computer-based systems. A decision class analysis is a collective analysis of a group of decisions that provides the high-level specification for such a computer system. This paper presents a decision class analysis of critical care life-support decisions. Key elements of this analysis are: the simplification of an otherwise extremely complex multistage sequential decision problem by using a sequence of two-stage models, and the use of six generic knowledge maps that capture the extremely complex relevant medical knowledge. PMID:8326214

  1. DECISION SUPPORT FRAMEWORK FOR STORMWATER MANAGEMENT IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) is developing a decision support system for placement of BMPs at strategic locations in urban watersheds. This tool wil...

  2. Interactive Decision Support for Academic Advising

    ERIC Educational Resources Information Center

    Mohamed, Abdallah

    2016-01-01

    Purpose: This paper aims to support academic advising, which plays a crucial role in student success and retention. The paper focuses on one of the most challenging tasks involved in academic advising: individual course scheduling. This task includes not only careful planning for different courses over several semesters according to students'…

  3. Clinical Decision Support Tools: The Evolution of a Revolution.

    PubMed

    Mould, D R; D'Haens, G; Upton, R N

    2016-04-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug monitoring. In the treatment of inflammatory bowel disease patients with infliximab, dashboards may reduce therapeutic failures and treatment costs. The history and future development of modern Bayesian dashboard systems is described. PMID:26785109

  4. Personalizing Drug Selection Using Advanced Clinical Decision Support

    PubMed Central

    Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A.; Glauser, Tracy

    2009-01-01

    This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States’ leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting. PMID:19898682

  5. Toward a synthesis of paradigms for decision support

    NASA Astrophysics Data System (ADS)

    Egner, Michael; Davis, Paul K.

    2004-08-01

    Over the past half-century, the study of human decision making has evolved from dry philosophy into a diverse set of experimentally-tested, behavior-centered theories. However, the sheer volume of disciplines and sub-disciplines-and the often-esoteric debates that divide them-threaten to obscure the very real advances that have been made in modeling human decision making. This paper, giving preliminary analysis from a longer study,[1] begins to address the "so-what" factor in decision making theory, specifically as related to Air Force modeling, simulation, and decision-support needs. While a general consensus is forming on how humans make decisions (descriptive), there are still major conflicts on how humans should make decisions (normative), and by extension, how human decision making can be improved (prescriptive). The first half of this paper surveys modern decision science, focusing on two of the most influential sub-disciplines: the heuristics & biases paradigm (HBP) and the naturalistic paradigm (NP). The second half of this paper will attempt to sketch out a normative/prescriptive synthesis between the two schools, and chart implications for design of decision support.

  6. Group decision support system for customer-driven product design

    NASA Astrophysics Data System (ADS)

    Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada

    2000-10-01

    This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.

  7. System-Agnostic Clinical Decision Support Services: Benefits and Challenges for Scalable Decision Support

    PubMed Central

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors’ formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors’ experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems. PMID:21603281

  8. Automated revision of CLIPS rule-bases

    NASA Technical Reports Server (NTRS)

    Murphy, Patrick M.; Pazzani, Michael J.

    1994-01-01

    This paper describes CLIPS-R, a theory revision system for the revision of CLIPS rule-bases. CLIPS-R may be used for a variety of knowledge-base revision tasks, such as refining a prototype system, adapting an existing system to slightly different operating conditions, or improving an operational system that makes occasional errors. We present a description of how CLIPS-R revises rule-bases, and an evaluation of the system on three rule-bases.

  9. Decision support system for theater missile defense

    NASA Astrophysics Data System (ADS)

    Gonsalves, Paul; Burge, Janet; Popp, Ben

    2003-08-01

    Military services require C4I systems that support a full spectrum of operations. This is specifically relevant to the theatre missile defense (TMD) mission planning and analysis community where there have been several recent concept changes; advancements in information technology, sensors, and weapons; and expansion in the diversity and capabilities of potential adversaries. To fully support campaign development and analysis in this new environment, there is a need for systems and tools that enhance understanding of adversarial behavior, assess potential threat capabilities and vulnerabilities, perform C4I system trades, and provide methods to identify macro-level novel or emergent combat tactics and behavior derived from simpler micro-level rules. Such systems must also be interactive, collaborative, and semi-autonomous, providing the INTEL analyst with the means for exploration and potential exploitation of novel enemy behavior patterns. To address these issues we have developed an Intelligent Threat Assessment Processor (ITAP) to provide prediction and interpretation of enemy courses of actions (eCOAs) for the TMD domain. This system uses a combination of genetic algorithm-based optimization in tandem with the spatial analysis and visualization capabilities of a commercial-off-the-shelf (COTS) geographic information system to generate and evaluate potential eCOAs.

  10. Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise

    PubMed Central

    Militello, Laura G.; Saleem, Jason J.; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Wolf, Steven P.; Doebbeling, Bradley N.

    2016-01-01

    Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration’s EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability. PMID:26973441

  11. Structured decision making as a method for linking quantitative decision support to community fundamental objectives

    EPA Science Inventory

    Decision support intended to improve ecosystem sustainability requires that we link stakeholder priorities directly to quantitative tools and measures of desired outcomes. Actions taken at the community level can have large impacts on production and delivery of ecosystem service...

  12. Reducing Diagnostic Error with Computer-Based Clinical Decision Support

    ERIC Educational Resources Information Center

    Greenes, Robert A.

    2009-01-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

  13. Developing a Decision Support System: The Software and Hardware Tools.

    ERIC Educational Resources Information Center

    Clark, Phillip M.

    1989-01-01

    Describes some of the available software and hardware tools that can be used to develop a decision support system implemented on microcomputers. Activities that should be supported by software are discussed, including data entry, data coding, finding and combining data, and data compatibility. Hardware considerations include speed, storage…

  14. Map-based decision aids for fire support

    NASA Astrophysics Data System (ADS)

    Yarosh, Victor

    1996-06-01

    The Fire Control Division at ARDEC is developing prototype decision aid tools to enable fire support echelons to rapidly respond to requests for fire support. Decision aids on fire support platforms can assist in route planning, site selection, and develop mobility overlays to enable the shooter to rapidly move into position and prepare for the fire mission. The Decision Aid system utilizes an integrated design approach which has each module interacting with the others by sharing data bases and common algorithms to provide recommended courses of action for route planning and generation, position selection, self defense, logistics estimates, situational awareness and fire mission planning aids such as tactical assessment, tactical planning, sustainment, etc. The Decision Aid system will use expert system artificial intelligence which will be developed from knowledge bases utilizing object oriented design. The modules currently reason on Defense Mapping Agency Interim Terrain Data and Digital Terrain Elevation Data and collect mission, intelligence, and sensor data from the digitized battlefield information distribution system to provide the crew or mission planners with intelligent recommendations. The system can provide a trade off analysis of time vs. safety, enable commanders to rapidly respond to fire support request, automatically generate OpOrders, and create overlays which depict mobility corridors, NBC areas, friendly units, overhead concealment, communications, and threat areas. The Decision Aids system can provide a vastly improved mobility, situational awareness, and decision cycle capabilities which can be utilized to increase the tempo of battle.

  15. Designing Computerized Decision Support That Works for Clinicians and Families

    PubMed Central

    Fiks, Alexander G.

    2011-01-01

    Evidence-based decision-making is central to the practice of pediatrics. Clinical trials and other biomedical research provide a foundation for this process, and practice guidelines, drawing from their results, inform the optimal management of an increasing number of childhood health problems. However, many clinicians fail to adhere to guidelines. Clinical decision support delivered using health information technology, often in the form of electronic health records, provides a tool to deliver evidence-based information to the point of care and has the potential to overcome barriers to evidence-based practice. An increasing literature now informs how these systems should be designed and implemented to most effectively improve outcomes in pediatrics. Through the examples of computerized physician order entry, as well as the impact of alerts at the point of care on immunization rates, the delivery of evidence-based asthma care, and the follow-up of children with attention deficit hyperactivity disorder, the following review addresses strategies for success in using these tools. The following review argues that, as decision support evolves, the clinician should no longer be the sole target of information and alerts. Through the Internet and other technologies, families are increasingly seeking health information and gathering input to guide health decisions. By enlisting clinical decision support systems to deliver evidence-based information to both clinicians and families, help families express their preferences and goals, and connect families to the medical home, clinical decision support may ultimately be most effective in improving outcomes. PMID:21315295

  16. Promoting Shared Decision Making in Disorders of Sex Development (DSD): Decision Aids and Support Tools.

    PubMed

    Siminoff, L A; Sandberg, D E

    2015-05-01

    Specific complaints and grievances from adult patients with disorders of sex development (DSD), and their advocates center around the lack of information or misinformation they were given about their condition and feeling stigmatized and shamed by the secrecy surrounding their condition and its management. Many also attribute poor sexual function to damaging genital surgery and/or repeated, insensitive genital examinations. These reports suggest the need to reconsider the decision-making process for the treatment of children born with DSD. This paper proposes that shared decision making, an important concept in adult health care, be operationalized for the major decisions commonly encountered in DSD care and facilitated through the utilization of decision aids and support tools. This approach may help patients and their families make informed decisions that are better aligned with their personal values and goals. It may also lead to greater confidence in decision making with greater satisfaction and less regret. A brief review of the past and current approach to DSD decision making is provided, along with a review of shared decision making and decision aids and support tools. A case study explores the need and potential utility of this suggested new approach.

  17. IBM’s Health Analytics and Clinical Decision Support

    PubMed Central

    Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

    2014-01-01

    Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

  18. Periodicals collection management using a decision support system

    SciTech Connect

    Compton, M.L.; Moser, E.C.

    1993-12-31

    Sandia National Laboratories is a multiprogram national laboratory established in 1949. The Library currently uses DOBIS for its automated system, including the Periodicals Control function for periodical check-in. DOBIS performs processing and control functions adequately, but could not meet our reporting needs. Therefore the Library`s Periodicals Decision Team decided that they needed another ``system`` for collection management. A Periodicals Decision Support System was created using information downloaded from DOBIS and uploaded into dBASE IV. The Periodical Decision Support System functions as an information-processing system that has aided us in making collection management decisions for periodicals. It certainly allows us to do interactive ad-hoc analysis; although there are no modeling tools currently incorporated in the system. We hope that these modeling tools will come later. We have been gathering information and developing needed reports to achieve this goal.

  19. Decision support methodology to establish priorities on the inspection of structures

    NASA Astrophysics Data System (ADS)

    Cortes, V. Juliette; Sterlacchini, Simone; Bogaard, Thom; Frigerio, Simone; Schenato, Luca; Pasuto, Alessandro

    2014-05-01

    For hydro-meteorological hazards in mountain areas, the regular inspection of check dams and bridges is important due to the effect of their functional status on water-sediment processes. Moreover, the inspection of these structures is time consuming for organizations due to their extensive number in many regions. However, trained citizen-volunteers can support civil protection and technical services in the frequency, timeliness and coverage of monitoring the functional status of hydraulic structures. Technicians should evaluate and validate these reports to get an index for the status of the structure. Thus, preventive actions could initiate such as the cleaning of obstructions or to pre-screen potential problems for a second level inspection. This study proposes a decision support methodology that technicians can use to assess an index for three parameters representing the functional status of the structure: a) condition of the structure at the opening of the stream flow, b) level of obstruction at the structure and c) the level of erosion in the stream bank. The calculation of the index for each parameter is based upon fuzzy logic theory to handle ranges in precision of the reports and to convert the linguistic rating scales into numbers representing the structure's status. A weighting method and multi-criteria method (Analytic Hierarchy Process- AHP and TOPSIS), can be used by technicians to combine the different ratings according to the component elements of the structure and the completeness of the reports. Finally, technicians can set decision rules based on the worst rating and a threshold for the functional indexes. The methodology was implemented as a prototype web-based tool to be tested with technicians of the Civil Protection in the Fella basin, Northern Italy. Results at this stage comprise the design and implementation of the web-based tool with GIS interaction to evaluate available reports and to set priorities on the inspection of structures

  20. ClinicalAccess: a clinical decision support tool.

    PubMed

    Crowell, Karen; Vardell, Emily

    2015-01-01

    ClinicalAccess is a new clinical decision support tool that uses a question-and-answer format to mirror clinical decision-making strategies. The unique format of ClinicalAccess delivers concise, authoritative answers to more than 120,000 clinical questions. This column presents a review of the product, a sample search, and a comparison with other point-of-care search engines.

  1. Application of GIS in foreign direct investment decision support system

    NASA Astrophysics Data System (ADS)

    Zhou, Jianlan; Sun, Koumei

    2007-06-01

    It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

  2. DocBot: a novel clinical decision support algorithm.

    PubMed

    Ninh, Andrew Q

    2014-01-01

    DocBot is a web-based clinical decision support system (CDSS) that uses patient interaction and electronic health record analytics to assist medical practitioners with decision making. It consists of two distinct HTML interfaces: a preclinical form wherein a patient inputs symptomatic and demographic information, and an interface wherein a medical practitioner views patient information and analysis. DocBot comprises an improved software architecture that uses patient information, electronic health records, and etiologically relevant binary decision questions (stored in a knowledgebase) to provide medical practitioners with information including, but not limited to medical assessments, treatment plans, and specialist referrals.

  3. Modular analytics management architecture for interoperability and decision support

    NASA Astrophysics Data System (ADS)

    Marotta, Stephen; Metzger, Max; Gorman, Joe; Sliva, Amy

    2016-05-01

    The Dual Node Decision Wheels (DNDW) architecture is a new approach to information fusion and decision support systems. By combining cognitive systems engineering organizational analysis tools, such as decision trees, with the Dual Node Network (DNN) technical architecture for information fusion, the DNDW can align relevant data and information products with an organization's decision-making processes. In this paper, we present the Compositional Inference and Machine Learning Environment (CIMLE), a prototype framework based on the principles of the DNDW architecture. CIMLE provides a flexible environment so heterogeneous data sources, messaging frameworks, and analytic processes can interoperate to provide the specific information required for situation understanding and decision making. It was designed to support the creation of modular, distributed solutions over large monolithic systems. With CIMLE, users can repurpose individual analytics to address evolving decision-making requirements or to adapt to new mission contexts; CIMLE's modular design simplifies integration with new host operating environments. CIMLE's configurable system design enables model developers to build analytical systems that closely align with organizational structures and processes and support the organization's information needs.

  4. Recent developments associated with decision support systems in water resources

    NASA Astrophysics Data System (ADS)

    Watkins, David W.; McKinney, Daene C.

    1995-07-01

    In order to limit the scope of this review, a working definition of a decision support system is needed. L. Adelman has defined decision support systems (DSSs) as "interactive computer programs that utilize analytical methods, such as decision analysis, optimization algorithms, program scheduling routines, and so on, for developing models to help decision makers formulate alternatives, analyze their impacts, and interpret and select appropriate options for implementation" (Adelman [1992], p. 2). Another definition has been offered by S. J. Andriole, who defined decision support as consisting of "any and all data, information, expertise or activities that contribute to option selection" (Andriole [1989], p. 3). A common idea explicit in each of these definitions is that DSSs integrate various technologies and aid in option selection. Implicit in each definition is that these are options for solving relatively large, unstructured problems. Thus, the following working definition of a DSS will be used in this review: A DSS is an integrated, interactive computer system, consisting of analytical tools and information management capabilities, designed to aid decision makers in solving relatively large, unstructured problems.

  5. Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

    PubMed

    Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

    2015-07-01

    Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting. PMID:26066306

  6. Temporal pattern mining for multivariate clinical decision support.

    PubMed

    Saini, Sheetal; Dua, Sumeet

    2013-01-01

    Multivariate temporal data are collections of contiguous data values that reflect complex temporal changes over a given duration. Technological advances have resulted in significant amounts of such data in high-throughput disciplines, including EEG and iEEG data for effective and efficient healthcare informatics, and decision support. Most data analytics and data-mining algorithms are effective in capturing global trends, but fail to capture localized behavioral changes in large temporal data sets. We present a two-step algorithmic methodology to uncover temporal patterns and exploiting them for an efficient and accurate decision support system. This methodology aids the discovery of previously unknown, nontrivial, and potentially useful temporal patterns for enhanced patient-specific clinical decision support with high degrees of sensitivity and specificity. Classification results on multivariate time series iEEG data for epileptic seizure detection also demonstrate the efficacy and accuracy of the technique to uncover interesting and effective domain class-specific temporal patterns.

  7. Aeromedical evacuation planning using geospatial decision-support.

    PubMed

    Bastian, Nathaniel D; Fulton, Lawrence V

    2014-02-01

    In this study, we proffer an algorithmic, geospatial-based decision-support methodology that assists military decision-makers in determining which aeromedical evacuation (MEDEVAC) assets to launch after receiving an injury location, given knowledge only of terrain, aircraft location, and aircraft capabilities. The objective is for military medical planners to use this decision-support tool (1) to improve real-time situational awareness by visualization of MEDEVAC coverage, showing which areas can be reached within established timelines; (2) to support medical planning by visualizing the impact of changes in the medical footprint to the MEDEVAC coverage; and (3) to support decision-making by providing a time-sorted list of MEDEVAC asset packages to select from, given the location of the patients. This same geospatial-based decision tool can be used for proper emplacement of evacuation assets such that the theater is covered within a truly representative 1-hour response time. We conclude with a discussion of applicability of this tool in medical force structure planning.

  8. Decision Support Systems for Research and Management in Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Rodriquez, Luis F.

    2004-01-01

    Decision support systems have been implemented in many applications including strategic planning for battlefield scenarios, corporate decision making for business planning, production planning and control systems, and recommendation generators like those on Amazon.com(Registered TradeMark). Such tools are reviewed for developing a similar tool for NASA's ALS Program. DSS are considered concurrently with the development of the OPIS system, a database designed for chronicling of research and development in ALS. By utilizing the OPIS database, it is anticipated that decision support can be provided to increase the quality of decisions by ALS managers and researchers.

  9. Judgmental biases in decision support for strike operations

    NASA Astrophysics Data System (ADS)

    Kulick, Jonathan D.; Davis, Paul K.

    2003-09-01

    Human decisionmaking does not typically fit the classical analytic model, and the heuristics employed may yield a variety of biased judgments. These biases are often considered inherently adverse, but may be functional in some cases. Decision support systems can mitigate some biases, but often introduce others. "Debiasing" decision support systems entails designing DSS to address expected biases, and to preclude inducing new ones. High-level C2 decisionmaking processes are poorly understood, but these general principles and lessons learned in other fields are expected to obtain. A notional air campaign illustrates potential biases in a commander"s judgment during planning and execution, and the role of debiasing operational DSS.

  10. E-DECIDER Decision Support Gateway For Earthquake Disaster Response

    NASA Astrophysics Data System (ADS)

    Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

    2013-12-01

    Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that

  11. Decision Support Systems and the Conflict Model of Decision Making: A Stimulus for New Computer-Assisted Careers Guidance Systems.

    ERIC Educational Resources Information Center

    Ballantine, R. Malcolm

    Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…

  12. Improving the Slum Planning Through Geospatial Decision Support System

    NASA Astrophysics Data System (ADS)

    Shekhar, S.

    2014-11-01

    In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

  13. Decision Support Model for Introduction of Gamification Solution Using AHP

    PubMed Central

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

  14. Decision support model for introduction of gamification solution using AHP.

    PubMed

    Kim, Sangkyun

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

  15. Technology Infusion Challenges from a Decision Support Perspective

    NASA Technical Reports Server (NTRS)

    Adumitroaie, V.; Weisbin, C. R.

    2009-01-01

    In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

  16. A fuzzy rule based metamodel for monthly catchment nitrate fate simulations

    NASA Astrophysics Data System (ADS)

    van der Heijden, S.; Haberlandt, U.

    2015-12-01

    The high complexity of nitrate dynamics and corresponding deterministic models make it very appealing to employ easy, fast, and parsimonious modelling alternatives for decision support. This study presents a fuzzy rule based metamodel consisting of eight fuzzy modules, which is able to simulate nitrate fluxes in large watersheds from their diffuse sources via surface runoff, interflow, and base flow to the catchment outlet. The fuzzy rules are trained on a database established with a calibrated SWAT model for an investigation area of 1000 km2. The metamodel performs well on this training area and on two out of three validation areas in different landscapes, with a Nash-Sutcliffe coefficient of around 0.5-0.7 for the monthly nitrate calculations. The fuzzy model proves to be fast, requires only few readily available input data, and the rule based model structure facilitates a common-sense interpretation of the model, which deems the presented approach suitable for the development of decision support tools.

  17. g.infer: A GRASS GIS module for rule-based data-driven classification and workflow control.

    NASA Astrophysics Data System (ADS)

    Löwe, Peter

    2013-04-01

    This poster describes the internal architecture of the new GRASS GIS module g.infer [1] and demonstrates application scenarios . The new module for GRASS GIS Version 6.x and 7.x enables rule-based analysis and workflow management via data-driven inference processes based on the C Language Integrated Production System (CLIPS) [2]. g.infer uses the pyClips module [3] to provide an Python-based environment for CLIPS within the GRASS GIS environment for rule-based knowledge engineering. Application scenarios range from rule-based classification tasks, event-driven workflow-control to complex simulations for tasks such as Soil Erosion Monitoring and Disaster Early Warning [4]. References: [1] Löwe P.: Introducing the new GRASS module g.infer for data-driven rule-based applications, Vol.8 2012-08, Geoinformatics FCE CTU, ISSN 1802-2669 [2] http://clipsrules.sourceforge.net/ [3] http://pyclips.sourceforge.net/web/ [4] Löwe P.: A Spatial Decision Support System for Radar-metereology Data in South Africa, Transactions in GIS 2004, (2): 235-244

  18. A fuzzy rule based metamodel for monthly catchment nitrate fate simulations

    NASA Astrophysics Data System (ADS)

    van der Heijden, Sven; Haberlandt, Uwe

    2014-05-01

    The high complexity of nitrate dynamics and corresponding deterministic models make it complicated to find suitable tools for decision support (DS) in large river catchments. Models for DS should ideally be easily applicable, fast, parsimonious in data requirements, easy to understand even for non-experts, able to reproduce sub-annual nitrate dynamics in order to evaluate temporal mitigation measures, and capable of scenario analysis. All these characteristics can be met with fuzzy rule based modelling. As a machine learning technique fuzzy rules have to be trained on data. Especially for nitrate, rarely enough data in sufficient temporal and spatial resolution is available. To circumvent this problem, the metamodelling approach can be used to train the fuzzy rules. This means a well-calibrated deterministic catchment model is used to generate "observed" data, which in a second step serve as training data for the fuzzy model. This study presents a fuzzy rule based metamodel consisting of eight fuzzy modules, which is able to simulate nitrate fluxes in large watersheds from their diffuse sources via surface runoff, interflow, and base flow to the catchment outlet. The fuzzy rules are trained on a database established with a calibrated SWAT model for an investigation area of 1000 km². The metamodel performs well on this training area and on two out of three validation areas in different landscapes, with a Nash-Sutcliffe coefficient around 0.5-0.7 for the monthly calculations. The fuzzy model proves to be fast, requires only few readily available input data, and the rule based model structure can be interpreted to a certain degree, which deems the presented approach suitable for the development of decision support tools.

  19. Distributed decision support for the 21st century mission space

    NASA Astrophysics Data System (ADS)

    McQuay, William K.

    2002-07-01

    The past decade has produced significant changes in the conduct of military operations: increased humanitarian missions, asymmetric warfare, the reliance on coalitions and allies, stringent rules of engagement, concern about casualties, and the need for sustained air operations. Future mission commanders will need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Integral to this process is creating situational assessment-understanding the mission space, simulation to analyze alternative futures, current capabilities, planning assessments, course-of-action assessments, and a common operational picture-keeping everyone on the same sheet of paper. Decision support tools in a distributed collaborative environment offer the capability of decomposing these complex multitask processes and distributing them over a dynamic set of execution assets. Decision support technologies can semi-automate activities, such as planning an operation, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that is not currently fused. The marriage of information and simulation technologies provides the mission commander with a collaborative virtual environment for planning and decision support.

  20. Data Mining and Data Fusion for Enhanced Decision Support

    SciTech Connect

    Khan, Shiraj; Ganguly, Auroop R; Gupta, Amar

    2008-01-01

    The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.

  1. Behavior-aware decision support systems : LDRD final report.

    SciTech Connect

    Hirsch, Gary B.; Homer, Jack; Chenoweth, Brooke N.; Backus, George A.; Strip, David R.

    2007-11-01

    As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.

  2. A Decision Support System for Solving Multiple Criteria Optimization Problems

    ERIC Educational Resources Information Center

    Filatovas, Ernestas; Kurasova, Olga

    2011-01-01

    In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…

  3. Team Machine: A Decision Support System for Team Formation

    ERIC Educational Resources Information Center

    Bergey, Paul; King, Mark

    2014-01-01

    This paper reports on the cross-disciplinary research that resulted in a decision-support tool, Team Machine (TM), which was designed to create maximally diverse student teams. TM was used at a large United States university between 2004 and 2012, and resulted in significant improvement in the performance of student teams, superior overall balance…

  4. DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) initiated a research in 2003 to develop a decision support system for placement of BMPs at strategic locations in urban ...

  5. Integrated decision support tools for Puget Sound salmon recovery planning

    EPA Science Inventory

    We developed a set of tools to provide decision support for community-based salmon recovery planning in Salish Sea watersheds. Here we describe how these tools are being integrated and applied in collaboration with Puget Sound tribes and community stakeholders to address restora...

  6. A Web-Based Decision Support Tool for Academic Advising

    ERIC Educational Resources Information Center

    Feghali, Tony; Zbib, Imad; Hallal, Sophia

    2011-01-01

    Student advising is an important and time-consuming effort in academic life. This paper attempts to solve a technology-based "last mile" problem by developing and evaluating a web-based decision support tool (the Online Advisor) that helps advisors and students make better use of an already present university student information system. Two…

  7. A decision support system for rainfed agricultural areas of Mexico

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rural inhabitants of arid lands lack sufficient water to fulfill their agricultural and household needs. They do not have readily available technical information to support decisions regarding the course of action they should follow to handle the agro-climatic risk. In this paper, a computer model (...

  8. Supporting Parental Decisions About Genomic Sequencing for Newborn Screening: The NC NEXUS Decision Aid.

    PubMed

    Lewis, Megan A; Paquin, Ryan S; Roche, Myra I; Furberg, Robert D; Rini, Christine; Berg, Jonathan S; Powell, Cynthia M; Bailey, Donald B

    2016-01-01

    Advances in genomic sequencing technology have raised fundamental challenges to the traditional ways genomic information is communicated. These challenges will become increasingly complex and will affect a much larger population in the future if genomics is incorporated into standard newborn screening practice. Clinicians, public health officials, and other stakeholders will need to agree on the types of information that they should seek and communicate to parents. Currently, few evidence-based and validated tools are available to support parental informed decision-making. These tools will be necessary as genomics is integrated into clinical practice and public health systems. In this article we describe how the North Carolina Newborn Exome Sequencing for Universal Screening study is addressing the need to support parents in making informed decisions about the use of genomic testing in newborn screening. We outline the context for newborn screening and justify the need for parental decision support. We also describe the process of decision aid development and the data sources, processes, and best practices being used in development. By the end of the study, we will have an evidenced-based process and validated tools to support parental informed decision-making about the use of genomic sequencing in newborn screening. Data from the study will help answer important questions about which genomic information ought to be sought and communicated when testing newborns. PMID:26729698

  9. Supporting Parental Decisions About Genomic Sequencing for Newborn Screening: The NC NEXUS Decision Aid

    PubMed Central

    Lewis, Megan A.; Paquin, Ryan S.; Roche, Myra I.; Furberg, Robert D.; Rini, Christine; Berg, Jonathan S.; Powell, Cynthia M.; Bailey, Donald B.

    2016-01-01

    Advances in genomic sequencing technology have raised fundamental challenges to the traditional ways genomic information is communicated. These challenges will become increasingly complex and will affect a much larger population in the future if genomics is incorporated into standard newborn screening practice. Clinicians, public health officials, and other stakeholders will need to agree on the types of information that they should seek and communicate to parents. Currently, few evidence-based and validated tools are available to support parental informed decision-making. These tools will be necessary as genomics is integrated into clinical practice and public health systems. In this article we describe how the North Carolina Newborn Exome Sequencing for Universal Screening study is addressing the need to support parents in making informed decisions about the use of genomic testing in newborn screening. We outline the context for newborn screening and justify the need for parental decision support. We also describe the process of decision aid development and the data sources, processes, and best practices being used in development. By the end of the study, we will have an evidenced-based process and validated tools to support parental informed decision-making about the use of genomic sequencing in newborn screening. Data from the study will help answer important questions about which genomic information ought to be sought and communicated when testing newborns. PMID:26729698

  10. Tools to support evidence-informed public health decision making

    PubMed Central

    2014-01-01

    Background Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. Methods As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Results Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the ‘actionable message(s)’ from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing

  11. A Decision Support System for Concrete Bridge Maintenance

    NASA Astrophysics Data System (ADS)

    Rashidi, Maria; Lemass, Brett; Gibson, Peter

    2010-05-01

    The maintenance of bridges as a key element in transportation infrastructure has become a major concern for asset managers and society due to increasing traffic volumes, deterioration of existing bridges and well-publicised bridge failures. A pivotal responsibility for asset managers in charge of bridge remediation is to identify the risks and assess the consequences of remediation programs to ensure that the decisions are transparent and lead to the lowest predicted losses in recognized constraint areas. The ranking of bridge remediation treatments can be quantitatively assessed using a weighted constraint approach to structure the otherwise ill-structured phases of problem definition, conceptualization and embodiment [1]. This Decision Support System helps asset managers in making the best decision with regards to financial limitations and other dominant constraints imposed upon the problem at hand. The risk management framework in this paper deals with the development of a quantitative intelligent decision support system for bridge maintenance which has the ability to provide a source for consistent decisions through selecting appropriate remediation treatments based upon cost, service life, product durability/sustainability, client preferences, legal and environmental constraints. Model verification and validation through industry case studies is ongoing.

  12. Computerized decision support system for kidney paired donation program.

    PubMed

    Chen, Yanhua; Song, Peter X-K

    2011-01-01

    In order to assist physicians and other health professionals for health care improvement, clinical decision support systems, through interactive computerized software, become very popular in clinical practice. The crisis associated with kidney organ shortage has triggered an innovative strategy, termed as Kidney Paired Donation (KPD) program, to address a rapidly expanding demand for donor kidneys. KPD program involves how to making optimal decision for allowing patients with incompatible living donors to receive compatible organs by best matching donors. Although some computerized optimization tools are being used in the current KPD program, there still lacks a general decision support system which enables us to evaluate and compare different kidney allocation strategies and effects of policy. In this paper, we discuss a general computer-based KPD decision model that appropriately reflects the real world clinical application. Also, the whole decision process is to be visualized by our Graphical User Interface (GUI) software, which offers a user friendly platform not only to provide a convenient interface for clinicians but also to assess different kidney exchange strategies of clinical importance. PMID:22255013

  13. Supporting registration decisions during 3D medical volume reconstructions

    NASA Astrophysics Data System (ADS)

    Bajcsy, Peter; Lee, Sang-Chul; Clutter, David

    2006-03-01

    We propose a methodology for making optimal registration decisions during 3D volume reconstruction in terms of (a) anticipated accuracy of aligned images, (b) uncertainty of obtained results during the registration process, (c) algorithmic repeatability of alignment procedure, and (d) computational requirements. We researched and developed a web-enabled, web services based, data-driven, registration decision support system. The registration decisions include (1) image spatial size (image sub-area or entire image), (2) transformation model (e.g., rigid, affine or elastic), (3) invariant registration feature (intensity, morphology or a sequential combination of the two), (4) automation level (manual, semi-automated, or fully-automated), (5) evaluations of registration results (multiple metrics and methods for establishing ground truth), and (6) assessment of resources (computational resources and human expertise, geographically local or distributed). Our goal is to provide mechanisms for evaluating the tradeoffs of each registration decision in terms of the aforementioned impacts. First, we present a medical registration methodology for making registration decisions that lead to registration results with well-understood accuracy, uncertainty, consistency and computational complexity characteristics. Second, we have built software tools that enable geographically distributed researchers to optimize their data-driven registration decisions by using web services and supercomputing resources. The support developed for registration decisions about 3D volume reconstruction is available to the general community with the access to the NCSA supercomputing resources. We illustrate performance by considering 3D volume reconstruction of blood vessels in histological sections of uveal melanoma from serial fluorescent labeled paraffin sections labeled with antibodies to CD34 and laminin. The specimens are studied by fluorescence confocal laser scanning microscopy (CLSM) images.

  14. Physician characteristics associated with decisions to withdraw life support.

    PubMed Central

    Christakis, N A; Asch, D A

    1995-01-01

    OBJECTIVE. This study was undertaken to identify attributes of physicians associated with physicians' decisions to withdraw life support. METHODS. Of the 862 Pennsylvania internists surveyed and asked to make decisions in response to hypothetical vignettes and to report their actual experience with the withdrawal of life support, 485 (56%) responded. The data were analyzed with regression models. RESULTS. With other factors controlled, physicians were more willing to withdraw life support if they were young, practiced in a tertiary care setting, or spent more time in clinical practice; they were less willing if they were Catholic or Jewish. Physicians reported a higher frequency of actually withdrawing life support if they were young, had more contact with ICU patients, spent more time in clinical practice, or were specialists. Physicians with a greater willingness to withdraw were more likely to report having done so. CONCLUSIONS. Physicians' personal characteristics are associated with both their preferences and their practice in the withdrawal of life support, and a greater willingness to withdraw is associated with a higher frequency of withdrawal. The influence of physician characteristics demonstrates that patient preferences and clinical circumstances do not exclusively govern such ethical decisions. PMID:7892921

  15. Needs assessment for diagnostic decision support systems (DDSS).

    PubMed Central

    Berner, E. S.; Shugerman, A. A.

    1991-01-01

    Diagnostic decision support systems are often developed without a clear idea of how well the system will meet the needs of its users. The present study was designed to assess the information needs of clinicians. A set of questions submitted to an information service by family physicians was used to determine how much need there was for diagnostic decision support, the types of support needed, and the general content areas of their questions. Results showed that less than half of the questions were related to diagnosis and that most of those were requests for general information about a given condition. In addition, the fewest diagnosis questions were for conditions that were seen frequently in ambulatory care in a survey of family practitioners. PMID:1807674

  16. Decision support for simulation-based operation planning

    NASA Astrophysics Data System (ADS)

    Schubert, Johan; Hörling, Pontus

    2016-05-01

    In this paper, we develop methods for analyzing large amounts of data from a military ground combat simulation system. Through a series of processes, we focus the big data set on situations that correspond to important questions and show advantageous outcomes. The result is a decision support methodology that provides commanders with results that answer specific questions of interest, such as what the consequences for the Blue side are in various Red scenarios or what a particular Blue force can withstand. This approach is a step toward taking the traditional data farming methodology from its analytical view into a prescriptive operation planning context and a decision making mode.

  17. Virtual medical record implementation for enhancing clinical decision support.

    PubMed

    Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile

    2012-01-01

    Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.

  18. Semantic Interoperability in Clinical Decision Support Systems: A Systematic Review.

    PubMed

    Marco-Ruiz, Luis; Bellika, Johan Gustav

    2015-01-01

    The interoperability of Clinical Decision Support (CDS) systems with other health information systems has become one of the main limitations to their broad adoption. Semantic interoperability must be granted in order to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of CDS systems. We performed a literature review to identify and provide an overview of the available standards that enable CDS interoperability in the areas of clinical information, decision logic, terminology, and web service interfaces. PMID:26262260

  19. Computing probability masses in rule-based systems

    SciTech Connect

    Dillard, R.A.

    1982-09-01

    This report describes a method of computing confidences in rule-based inference systems by using the Dempster-Shafter theory. The theory is applicable to tactical decision problems which can be formulated in terms of sets of exhaustive and mutually exclusive propositions. Dempster's combining procedure, a generalization of Bayesian inference, can be used to combine probability mass assignments supplied by independent bodies of evidence. This report describes the use of Dempster's combining method and Shafer's representation framework in rule-based inference systems. It is shown that many kinds of data fusion problems can be represented in a way such that the constraints are met. Although computational problems remain to be solved, the theory should provide a versatile and consistent way of combining confidences for a large class of inferencing problems.

  20. Perspectives on the use of rule-based control

    NASA Technical Reports Server (NTRS)

    Handelman, David A.; Stengel, Robert F.

    1990-01-01

    Issues regarding the application of artificial intelligence techniques to real-time control are discussed. Advantages associated with knowledge-based programming are discussed. A proposed rule-based control technique is summarized and applied to the problem of automated aircraft emergency procedure execution. Although emergency procedures are by definition predominately procedural, their numerous evaluation and decision points make a declarative representation of the knowledge they encode highly attractive, resulting in an organized and easily maintained software hierarchy. Simulation results demonstrate that real-time performance can be obtained using a microprocessor-based controller. It is concluded that a rule-based control system design approach may prove more useful than conventional methods under certain circumstances, and that declarative rules with embedded procedural code provide a sound basis for the construction of complex, yet economical, control systems.

  1. Decision blocks: A tool for automating decision making in CLIPS

    NASA Technical Reports Server (NTRS)

    Eick, Christoph F.; Mehta, Nikhil N.

    1991-01-01

    The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program.

  2. A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context

    NASA Astrophysics Data System (ADS)

    Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul

    Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.

  3. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  4. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    R. L. Hoskinson; J. R. Hess; R. K. Fink

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  5. Hospital management decision support: a balanced scorecard approach.

    PubMed

    Gordon, D; Chapman, R; Kunov, H; Dolan, A; Carter, M

    1998-01-01

    Hospital management teams receive voluminous data from a wide variety of sources, but are unable to distill the essential data they require to make good decisions. We have used a methodology, which helps teams define and use important management data coupled with an information system that makes this data accessible. Results of our evaluation indicate that the process of developing a Balanced Scorecard indicator system helps management teams to define meaningful strategic objectives and measurable performance indicators. The framework combined with the information acts as an integrating force, providing a shared understanding of the unit's goals. We conclude that a customized decision support system, which integrates multiple measures in a balanced Scorecard framework, is a powerful tool for enabling complex decision making by a management team. PMID:10384497

  6. Middle Mississippi River decision support system: user's manual

    USGS Publications Warehouse

    Rohweder, Jason J.; Zigler, Steven J.; Fox, Timothy J.; Hulse, Steven N.

    2005-01-01

    This user's manual describes the Middle Mississippi River Decision Support System (MMRDSS) and gives detailed examples on its use. The MMRDSS provides a framework to assist decision makers regarding natural resource issues in the Middle Mississippi River floodplain. The MMRDSS is designed to provide users with a spatially explicit tool for tasks, such as inventorying existing knowledge, developing models to investigate the potential effects of management decisions, generating hypotheses to advance scientific understanding, and developing scientifically defensible studies and monitoring. The MMRDSS also includes advanced tools to assist users in evaluating differences in complexity, connectivity, and structure of aquatic habitats among river reaches. The Environmental Systems Research Institute ArcView 3.x platform was used to create and package the data and tools of the MMRDSS.

  7. Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

    NASA Technical Reports Server (NTRS)

    Tavana, Madjid

    1995-01-01

    The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

  8. A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

    ERIC Educational Resources Information Center

    Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

    2015-01-01

    In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

  9. Human Decision Processes: Implications for SSA Support Tools

    NASA Astrophysics Data System (ADS)

    Picciano, P.

    2013-09-01

    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.

  10. Reducing diagnostic error with computer-based clinical decision support.

    PubMed

    Greenes, Robert A

    2009-09-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision making (Schiff). In addition, several other considerations relating to this topic are interesting to ponder. We are moving toward increased understanding of gene regulation and gene expression, identification of biomarkers, and the ability to predict patient response to disease and to tailor treatments to these individual variations-referred to as "personalized" or, more recently, "predictive" medicine. Consequently, diagnostic decision making is more and more linked to management decision making, and generic diagnostic labels like "diabetes" or "colon cancer" will no longer be sufficient, because they don't tell us what to do. Ultimately, if we have more complete data including more structured capture of phenomic data as well as the characterization of the patient's genome, direct prediction from responses of highly refined subsets of similar patients in a database can be used to select appropriate management, the effectiveness of which was demonstrated in projects in selected limited domains as early as the 1970s. In general, there are six classes of methodologies, including the above, which can be applied to delivering CDS. In addition, patients are becoming more knowledgeable and should be regarded as active participants, not only in helping to obtain data but also in their own status assessment and as recipients of decision support. With the above advances, this is a very promising time to be engaged in pursuit of methods of CDS. PMID:19669915

  11. Apply creative thinking of decision support in electrical nursing record.

    PubMed

    Hao, Angelica Te-Hui; Hsu, Chien-Yeh; Li-Fang, Huang; Jian, Wen-Shan; Wu, Li-Bin; Kao, Ching-Chiu; Lu, Mei-Show; Chang, Her-Kung

    2006-01-01

    The nursing process consists of five interrelated steps: assessment, diagnosis, planning, intervention, and evaluation. In the nursing process, the nurse collects a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Computer systems are viewed as tools to expand the capabilities of the nurse's mind. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most fundamental decision support--i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to generate nursing diagnoses from data and how to individualize the care plans still reminds of the nurse. The purpose of this study is to develop a pilot structure in electronic nursing record system integrated with international nursing standard for improving the proficiency and accuracy of plan of care in clinical pathway process. The proposed pilot systems not only assist both student nurses and nurses who are novice in nursing practice, but also experts who need to work in a practice area which they are not familiar with.

  12. Supported decision making: a review of the international literature.

    PubMed

    Davidson, Gavin; Kelly, Berni; Macdonald, Geraldine; Rizzo, Maria; Lombard, Louise; Abogunrin, Oluwaseye; Clift-Matthews, Victoria; Martin, Alison

    2015-01-01

    Supported decision making (SDM) refers to the process of supporting people, whose decision making ability may be impaired, to make decisions and so promote autonomy and prevent the need for substitute decision making. There have been developments in SDM but mainly in the areas of intellectual disabilities and end-of-life care rather than in mental health. The main aim of this review was to provide an overview of the available evidence relevant to SDM and so facilitate discussion of how this aspect of law, policy and practice may be further developed in mental health services. The method used for this review was a Rapid Evidence Assessment which involved: developing appropriate search strategies; searching relevant databases and grey literature; then assessing, including and reviewing relevant studies. Included studies were grouped into four main themes: studies reporting stakeholders' views on SDM; studies identifying barriers to the implementation of SDM; studies highlighting ways to improve implementation; and studies on the impact of SDM. The available evidence on implementation and impact, identified by this review, is limited but there are important rights-based, effectiveness and pragmatic arguments for further developing and researching SDM for people with mental health problems.

  13. A Customized Drought Decision Support Tool for Hsinchu Science Park

    NASA Astrophysics Data System (ADS)

    Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin

    2016-04-01

    Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.

  14. Towards the ecotourism: a decision support model for the assessment of sustainability of mountain huts in the Alps.

    PubMed

    Stubelj Ars, Mojca; Bohanec, Marko

    2010-12-01

    This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists.

  15. What can Natural Language Processing do for Clinical Decision Support?

    PubMed Central

    Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.

    2009-01-01

    Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

  16. Decision support for subjects exposed to heat stress.

    PubMed

    Seeberg, Trine M; Vardøy, Astrid-Sofie B; Taklo, Maaike M Visser; Austad, Hanne Opsahl

    2013-03-01

    The physiological and activity strain index (PASI) has been developed to improve the online decision support for workers exposed to heat stress. Fire fighters (smoke divers) which are exposed to both heat-stress and high-risk situations have been used as test case. PASI combines a modified version of the relatively well-known physiological strain index (PSI) with activity data from accelerometers. The algorithm has been developed based on tests in a laboratory, and it has been verified in two field tests performed by smoke divers exposed to heat stress. The verification demonstrates that it is possible to distinguish between high- and low-risk situations when data from accelerometers are added to the situation analysis. This indicates that PASI can contribute to an improved risk assessment and online decision support for smoke divers compared to using PSI alone. PMID:24235112

  17. On the heuristic nature of medical decision-support systems.

    PubMed

    Aliferis, C F; Miller, R A

    1995-03-01

    In the realm of medical decision-support systems, the term "heuristic systems" is often considered to be synonymous with "medical artificial intelligence systems" or with "systems employing informal model(s) of problem solving". Such a view may be inaccurate and possibly impede the conceptual development of future systems. This article examines the nature of heuristics and the levels at which heuristic solutions are introduced during system design and implementation. The authors discuss why heuristics are ubiquitous in all medical decision-support systems operating at non-trivial domains, and propose a unifying definition of heuristics that encompasses formal and ad hoc systems. System developers should be aware of the heuristic nature of all problem solving done in complex real world domains, and characterize their own use of heuristics in describing system development and implementation. PMID:9082138

  18. A Flight Deck Decision Support Tool for Autonomous Airborne Operations

    NASA Technical Reports Server (NTRS)

    Ballin, Mark G.; Sharma, Vivek; Vivona, Robert A.; Johnson, Edward J.; Ramiscal, Ermin

    2002-01-01

    NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.

  19. Decision support system based semantic web for personalized patient care.

    PubMed

    Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine

    2012-01-01

    Personalized medicine may be considered an extension of traditional approaches to understanding and treating diseases, but with greater precision. A profile of a patient's genetic variation can guide the selection of drugs or treatment protocols that minimize harmful side effects or ensure a more successful outcome. In this paper we describe a decision support system designed to assist physicians for personalized care, and methodology for integration in the clinical workflow. A reasoning method for interacting heterogeneous knowledge and data is a necessity in the context of personalized medicine. Development of clinical decision support based semantic web for personalized patient care is to achieve its potential and improve the quality, safety and efficiency of healthcare.

  20. A decision support system for AIDS intervention and prevention.

    PubMed

    Xu, L D

    1994-08-01

    In recent years, the importance of information systems has been identified as a vital issue to continuing success in AIDS intervention and prevention (AIP). The advances in information technology have resulted in integrative information systems including decision support systems (DSS). The concept of DSS for AIP was created at the intersection of two trends. The first trend was a growing belief that AIP information systems are successful in automating operations in AIP programs. The second was a continuing improvement in modeling and software development in the AIP area. This paper presents an integrated DSS for AIP. The system is integrated with a database and achieves its efficiency by incorporating various algorithms and models to support AIP decision processes. The application examples include screening AIDS-risky behaviors, evaluating educational interventions, and scheduling AIP sessions. The implementation results present evidence of the usefulness of the system in AIP.

  1. Distributed collaborative decision support environments for predictive awareness

    NASA Astrophysics Data System (ADS)

    McQuay, William K.; Stilman, Boris; Yakhnis, Vlad

    2005-05-01

    The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy"s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep "look-ahead" from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.

  2. Emulation Modeling with Bayesian Networks for Efficient Decision Support

    NASA Astrophysics Data System (ADS)

    Fienen, M. N.; Masterson, J.; Plant, N. G.; Gutierrez, B. T.; Thieler, E. R.

    2012-12-01

    Bayesian decision networks (BDN) have long been used to provide decision support in systems that require explicit consideration of uncertainty; applications range from ecology to medical diagnostics and terrorism threat assessments. Until recently, however, few studies have applied BDNs to the study of groundwater systems. BDNs are particularly useful for representing real-world system variability by synthesizing a range of hydrogeologic situations within a single simulation. Because BDN output is cast in terms of probability—an output desired by decision makers—they explicitly incorporate the uncertainty of a system. BDNs can thus serve as a more efficient alternative to other uncertainty characterization methods such as computationally demanding Monte Carlo analyses and others methods restricted to linear model analyses. We present a unique application of a BDN to a groundwater modeling analysis of the hydrologic response of Assateague Island, Maryland to sea-level rise. Using both input and output variables of the modeled groundwater response to different sea-level (SLR) rise scenarios, the BDN predicts the probability of changes in the depth to fresh water, which exerts an important influence on physical and biological island evolution. Input variables included barrier-island width, maximum island elevation, and aquifer recharge. The variability of these inputs and their corresponding outputs are sampled along cross sections in a single model run to form an ensemble of input/output pairs. The BDN outputs, which are the posterior distributions of water table conditions for the sea-level rise scenarios, are evaluated through error analysis and cross-validation to assess both fit to training data and predictive power. The key benefit for using BDNs in groundwater modeling analyses is that they provide a method for distilling complex model results into predictions with associated uncertainty, which is useful to decision makers. Future efforts incorporate

  3. Disaster Management with a Next Generation Disaster Decision Support System

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2015-12-01

    As populations become increasingly concentrated in large cities, the world is experiencing an inevitably growing trend towards the urbanisation of disasters. Scientists have contributed significant advances in understanding the geophysical causes of natural hazards and have developed sophisticated tools to predict their effects; while, much less attention has been devoted to tools that increase situational awareness, facilitate leadership, provide effective communication channels and data flow and enhance the cognitive abilities of decision makers and first responders. In this paper, we envisioned the capabilities of a next generation disaster decision support system and hence proposed a state-of-the-art system architecture design to facilitate the decision making process in natural catastrophes such as flood and bushfire by utilising a combination of technologies for multi-channel data aggregation, disaster modelling, visualisation and optimisation. Moreover, we put our thoughts into action by implementing an Intelligent Disaster Decision Support System (IDDSS). The developed system can easily plug in to external disaster models and aggregate large amount of heterogeneous data from government agencies, sensor networks, and crowd sourcing platforms in real-time to enhance the situational awareness of decision makers and offer them a comprehensive understanding of disaster impacts from diverse perspectives such as environment, infrastructure and economy, etc. Sponsored by the Australian Government and the Victorian Department of Justice (Australia), the system was built upon a series of open-source frameworks (see attached figure) with four key components: data management layer, model application layer, processing service layer and presentation layer. It has the potential to be adopted by a range of agencies across Australian jurisdictions to assist stakeholders in accessing, sharing and utilising available information in their management of disaster events.

  4. Using Clinical Decision Support and Dashboard Technology to Improve Heart Team Efficiency and Accuracy in a Transcatheter Aortic Valve Implantation (TAVI) Program.

    PubMed

    Clarke, Sarah; Wilson, Marisa L; Terhaar, Mary

    2016-01-01

    Heart Team meetings are becoming the model of care for patients undergoing transcatheter aortic valve implantations (TAVI) worldwide. While Heart Teams have potential to improve the quality of patient care, the volume of patient data processed during the meeting is large, variable, and comes from different sources. Thus, consolidation is difficult. Also, meetings impose substantial time constraints on the members and financial pressure on the institution. We describe a clinical decision support system (CDSS) designed to assist the experts in treatment selection decisions in the Heart Team. Development of the algorithms and visualization strategy required a multifaceted approach and end-user involvement. An innovative feature is its ability to utilize algorithms to consolidate data and provide clinically useful information to inform the treatment decision. The data are integrated using algorithms and rule-based alert systems to improve efficiency, accuracy, and usability. Future research should focus on determining if this CDSS improves patient selection and patient outcomes. PMID:27332170

  5. Personalization and Patient Involvement in Decision Support Systems: Current Trends

    PubMed Central

    Sacchi, L.; Lanzola, G.; Viani, N.

    2015-01-01

    Summary Objectives This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods We considered papers published on scientific journals, by querying PubMed and Web of Science™. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Conclusions Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large. PMID:26293857

  6. An Advanced Decision Support Tool for Electricity Infrastructure Operations

    SciTech Connect

    Chen, Yousu; Huang, Zhenyu; Wong, Pak C.; Mackey, Patrick S.; Allwardt, Craig H.; Ma, Jian; Greitzer, Frank L.

    2010-01-31

    Electricity infrastructure, as one of the most critical infrastructures in the U.S., plays an important role in modern societies. Its failure would lead to significant disruption of people’s lives, industry and commercial activities, and result in massive economic losses. Reliable operation of electricity infrastructure is an extremely challenging task because human operators need to consider thousands of possible configurations in near real-time to choose the best option and operate the network effectively. In today’s practice, electricity infrastructure operation is largely based on operators’ experience with very limited real-time decision support, resulting in inadequate management of complex predictions and the inability to anticipate, recognize, and respond to situations caused by human errors, natural disasters, or cyber attacks. Therefore, a systematic approach is needed to manage the complex operational paradigms and choose the best option in a near-real-time manner. This paper proposes an advanced decision support tool for electricity infrastructure operations. The tool has the functions of turning large amount of data into actionable information to help operators monitor power grid status in real time; performing trend analysis to indentify system trend at the regional level or system level to help the operator to foresee and discern emergencies, studying clustering analysis to assist operators to identify the relationships between system configurations and affected assets, and interactively evaluating the alternative remedial actions to aid operators to make effective and timely decisions. This tool can provide significant decision support on electricity infrastructure operations and lead to better reliability in power grids. This paper presents examples with actual electricity infrastructure data to demonstrate the capability of this tool.

  7. 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.

  8. Demonstration of Decision Support Tools for Sustainable Development

    SciTech Connect

    Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.

    2000-11-01

    The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.

  9. The economic valuation of improved process plant decision support technology.

    PubMed

    White, Douglas C

    2007-06-01

    How can investments that would potentially improve a manufacturing plant's decision process be economically justified? What is the value of "better information," "more flexibility," or "improved integration" and the technologies that provide these effects? Technology investments such as improved process modelling, new real time historians and other databases, "smart" instrumentation, better data analysis and visualization software, and/or improved user interfaces often include these benefits as part of their valuation. How are these "soft" benefits to be converted to a quantitative economic return? Quantification is important if rational management decisions are to be made about the correct amount of money to invest in the technologies, and which technologies to choose among the many available ones. Modelling the plant operational decision cycle-detect, analyse, forecast, choose and implement--provides a basis for this economic quantification. In this paper a new economic model is proposed for estimation of the value of decision support investments based on their effect upon the uncertainty in forecasting plant financial performance. This model leads to quantitative benefit estimates that have a realistic financial basis. An example is presented demonstrating the application of the method.

  10. Bridging groundwater models and decision support with a Bayesian network

    USGS Publications Warehouse

    Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

    2013-01-01

    Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

  11. An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

    NASA Astrophysics Data System (ADS)

    Song, M.; Li, W.; Zhou, X.

    2014-12-01

    In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

  12. Decision support for integrated water-energy planning.

    SciTech Connect

    Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.

    2009-10-01

    Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.

  13. Intelligent decision support tool for supply chain planning

    NASA Astrophysics Data System (ADS)

    Li, Dong; Barnes, Cathy; Axtell, C.; McKay, Alison; de Pennington, Alan

    2001-10-01

    A decision support system using extended quality function deployment model (EQFDM) and internet application for manufacturing supply chain (SC) planning has been developed in this research. In this paper, a customer-focused quality evaluation approach, the EQFDM with internet application is employed to develop a coordinated planning system in SCs and assist mapping decisions of strategic planning into each partner's internal planning processes. To facilitate cooperation of SC partners in strategic planning, the hybrid planning process has been programmed into a web tool. The local planning has been supported by fuzzy logic approach so that approximate optimal solutions can be obtained avoiding difficulties of acquiring quantitative data. Through this intelligent Web based architecture, individual planning processes can be efficiently co-ordinated by means of efficient communication and visualizing consequences of a decision to be made on SC performance. Case study in a manufacturing (packaging) SC has been conducted to implement a scenario planning process for strategies on re-engineering the manufacturing SC. The research result shows that the intelligent system could be a promising tool for assisting strategic planning in a SC cooperation context.

  14. North Slope Decision Support for Water Resource Planning and Management

    SciTech Connect

    Schnabel, William; Brumbelow, Kelly

    2013-03-31

    The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.

  15. A highly scalable, interoperable clinical decision support service

    PubMed Central

    Goldberg, Howard S; Paterno, Marilyn D; Rocha, Beatriz H; Schaeffer, Molly; Wright, Adam; Erickson, Jessica L; Middleton, Blackford

    2014-01-01

    Objective To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. Materials and methods The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. Results The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. Discussion We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. Conclusions ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance. PMID:23828174

  16. Effects on Decision Quality of Supporting Multi-attribute Evaluation in Groups

    PubMed

    Timmermans; Vlek

    1996-11-01

    In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and were asked to reach a decision about the same problem. Groups received either MAU support or no support. Results show that for relatively simple problems the most effective method is to provide subjects with both individual and group decision support. Here, decision support had a clear impact on subjects' preferences and the level of agreement between group members. In addition, satisfaction with the decision and the decision procedure was relatively high. Overall, decision support improved communication; subjects reported to find the problem easier, to have more influence on the group decision, and to find it easier to express their opinions. For more complex problems, however, decision making without group support (whether preceded by individual support or not) was evaluated most favorably. Individual decision support in this condition was sometimes better than no support; i.e., there was a lower reported problem difficulty, a higher satisfaction with the group decision, and a higher reported influence on the group decision. The effectiveness of group MAU decision support for complex problems was evaluated less favorably.

  17. Classification of Contaminated Sites Using a Fuzzy Rule Based System

    SciTech Connect

    Lemos, F.L. de; Van Velzen, K.; Ross, T.

    2006-07-01

    This paper presents the general framework of a multi level model to manage contaminated sites that is being developed. A rule based system along with a scoring system for ranking sites for phase 1 ESA is being proposed (Level 1). Level 2, which consists of the recommendation of the consultant based on their phase 1 ESA is reasonably straightforward. Level 3 which consists of classifying sites which already had a phase 2 ESA conducted on them will involve a multi-objective decision making tool. Fuzzy set theory, which includes the concept of membership functions, was adjudged as the best way to deal with uncertain and non-random information. (authors)

  18. Use of Remote Sensing for Decision Support in Africa

    NASA Technical Reports Server (NTRS)

    Policelli, Frederick S.

    2007-01-01

    Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.

  19. Toward image analysis and decision support for ultrasound technology.

    PubMed

    Crofts, Gillian; Padman, Rema; Maharaja, Nisha

    2013-01-01

    Ultrasound is a low cost and efficient method of detecting diseases and abnormalities in the body. Yet there is a lack of precision and reliability associated with the technology, partly due to the operator dependent nature of ultrasound scanning. When scanning is performed to an agreed protocol, ultrasound has been shown to be highly reliable. This research aims to minimize these limitations that arise during ultrasound training, scanning and reporting by developing and evaluating an image analysis and decision support system that can aid the decision making process. We hypothesize that this intervention will likely increase the role of ultrasound in diagnosis when compared with other imaging technologies, particularly in low resource settings. PMID:23920862

  20. Water flow algorithm decision support tool for travelling salesman problem

    NASA Astrophysics Data System (ADS)

    Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd

    2016-08-01

    This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.

  1. Decision support for workload assessment - Introducing WC FIELDE

    NASA Technical Reports Server (NTRS)

    Casper, Patricia A.; Shively, Robert J.; Hart, Sandra G.

    1987-01-01

    Currently there is a great demand for mental workload evaluation in the course of system design and modification. In light of this demand, a microprocessor-based decision support system has been created called WC FIELDE: Workload Consultant for FIELD Evaluation. The system helps the user select workload measures appropriate to his or her application from the large pool of currently available techniques. Both novices and those with some workload experience may benefit from using WC FIELDE, since the system's operation is entirely transparent and all rules involved in the decision process are available for the user to examine. WC FIELDE recommends several assessment methodologies in decreasing order of appropriateness, and provides additional information on each measure at the end of the program in the form of text files.

  2. Decision System Integrating Preferences to Support Sleep Staging.

    PubMed

    Ugon, Adrien; Sedki, Karima; Kotti, Amina; Seroussi, Brigitte; Philippe, Carole; Ganascia, Jean-Gabriel; Garda, Patrick; Bouaud, Jacques; Pinna, Andrea

    2016-01-01

    Scoring sleep stages can be considered as a classification problem. Once the whole recording segmented into 30-seconds epochs, features, extracted from raw signals, are typically injected into machine learning algorithms in order to build a model able to assign a sleep stage, trying to mimic what experts have done on the training set. Such approaches ignore the advances in sleep medicine, in which guidelines have been published by the AASM, providing definitions and rules that should be followed to score sleep stages. In addition, these approaches are not able to solve conflict situations, in which criteria of different sleep stages are met. This work proposes a novel approach based on AASM guidelines. Rules are formalized integrating, for some of them, preferences allowing to support decision in conflict situations. Applied to a doubtful epoch, our approach has taken the appropriate decision. PMID:27577436

  3. Creating shareable decision support services: an interdisciplinary challenge.

    PubMed

    Paterno, Marilyn D; Maviglia, Saverio M; Ramelson, Harley Z; Schaeffer, Molly; Rocha, Beatriz H; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford; Goldberg, Howard S

    2010-01-01

    Creating shareable decision support services is a complex task requiring effort from multiple interdisciplinary role players with a wide variety of experience and expertise. The CDS Consortium research project has developed such a service, defining a multi-layer representation of knowledge and building upon an architectural service design created at Partners Health Care, and is demonstrating its use in both a local and an external institutional setting. The process was iterative, and we encountered unexpected requirements based on decisions made at various points. We report in this paper on challenges we faced while pursuing this research: knowledge representation and modeling, data interchange and standards adoption, the process of getting agreement on content, logistics of integrating into a system that already has multiple CDS interventions, legal issues around privacy and access, inter-team communication and organization.

  4. Impact of a decision-support tool on decision making at the district level in Kenya

    PubMed Central

    2013-01-01

    Background In many countries, the responsibility for planning and delivery of health services is devolved to the subnational level. Health programs, however, often fall short of efficient use of data to inform decisions. As a result, programs are not as effective as they can be at meeting the health needs of the populations they serve. In Kenya, a decision-support tool, the District Health Profile (DHP) tool was developed to integrate data from health programs, primarily HIV, at the district level and to enable district health management teams to review and monitor program progress for specific health issues to make informed service delivery decisions. Methods Thirteen in-depth interviews were conducted with ten tool users and three non-users in six districts to qualitatively assess the process of implementing the tool and its effect on data-informed decision making at the district level. The factors that affected use or non-use of the tool were also investigated. Respondents were selected via convenience sample from among those that had been trained to use the DHP tool except for one user who was self-taught to use the tool. Selection criteria also included respondents from urban districts with significant resources as well as respondents from more remote, under-resourced districts. Results Findings from the in-depth interviews suggest that among those who used it, the DHP tool had a positive effect on data analysis, review, interpretation, and sharing at the district level. The automated function of the tool allowed for faster data sharing and immediate observation of trends that facilitated data-informed decision making. All respondents stated that the DHP tool assisted them to better target existing services in need of improvement and to plan future services, thus positively influencing program improvement. Conclusions This paper stresses the central role that a targeted decision-support tool can play in making data aggregation, analysis, and presentation

  5. New Decision Support for Landslide and Other Disaster Events

    NASA Astrophysics Data System (ADS)

    Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.

    2013-12-01

    An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of

  6. Interactive decision-making support model in MOSD

    NASA Astrophysics Data System (ADS)

    Liu, Yang; Lan, Ze-ying; Liu, Yao-lin; Qin, Liang-jun

    2009-10-01

    The Multi-objective spatial optimization problem is common in the word, which usually has a set of non-dominated resolutions, also called Pareto resolutions, instead of a single ideal one. So, the Multi-objectives spatial decision support system (MOSDSS) has two vital basements: how to acquire all the Pareto resolutions by Multi-objective optimization arithmetic, and how to analysis and appraise the candidates to determinate the final satisfying solution. At present, there are abundant research fruit for the former problem, however the latter one hasn't attracted abroad attention in the field. Nowadays, the findings about analyzing and evaluating the Pareto resolutions mainly focus on three aspects: the visual expression of candidates, appraising the comparability among the solutions, and designing the prototype system of visual support tools, which are lack of systemic conclusion and summarization. Hence, this paper emphasizes the latter problem of MOSDSS and puts up an interactive decision-making support model to largely improve the efficiency of analyzing and evaluating the Pareto resolutions. This model is composed of 3 pivotal parts: the geographic brush mechanism, the similarity querying operators as well as the interactive searching method. Then, the paper designs a prototype system on the base of the model, which is successfully tested in the exam.

  7. Coordinating complex decision support activities across distributed applications

    NASA Technical Reports Server (NTRS)

    Adler, Richard M.

    1994-01-01

    Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

  8. A decision support system for assessing landfill performance.

    PubMed

    Celik, Başak; Girgin, Sertan; Yazici, Adnan; Unlü, Kahraman

    2010-01-01

    Designing environmentally sound landfills is a challenging engineering task due to complex interactions of numerous design variables; such as landfill size, waste characteristics, and site hydrogeology. Decision support systems (DSS) can be utilized to handle these complex interactions and to aid in a performance-based landfill design by coupling system simulation models (SSM). The aim of this paper is to present a decision support system developed for a performance-based landfill design. The developed DSS is called Landfill Design Decision Support System - LFDSS. A two-step DSS framework, composed of preliminary design and detailed design phases, is set to effectively couple and run the SSMs and calculation modules. In preliminary design phase, preliminary design alternatives are proposed using general site data. In detailed design phase, proposed design alternatives are further simulated under site-specific data using SSMs for performance evaluation. LFDSS calculates the required landfill volume, performs landfill base contour design, proposes preliminary design alternatives based on general site conditions, evaluates the performance of the proposed designs, calculates the factor of safety values for slope stability analyses, and performs major cost calculations. The DSS evaluates the results of all landfill design alternatives, and determines whether the design satisfies the predefined performance criteria. The DSS ultimately enables comparisons among different landfill designs based on their performances (i.e. leachate head stability, and groundwater contamination), constructional stability and costs. The developed DSS was applied to a real site, and the results demonstrated the strengths of the developed system on designing environmentally sound and feasible landfills.

  9. A decision support system for assessing landfill performance

    SciTech Connect

    Celik, Basak; Girgin, Sertan; Yazici, Adnan; Unlue, Kahraman

    2010-01-15

    Designing environmentally sound landfills is a challenging engineering task due to complex interactions of numerous design variables; such as landfill size, waste characteristics, and site hydrogeology. Decision support systems (DSS) can be utilized to handle these complex interactions and to aid in a performance-based landfill design by coupling system simulation models (SSM). The aim of this paper is to present a decision support system developed for a performance-based landfill design. The developed DSS is called Landfill Design Decision Support System - LFDSS. A two-step DSS framework, composed of preliminary design and detailed design phases, is set to effectively couple and run the SSMs and calculation modules. In preliminary design phase, preliminary design alternatives are proposed using general site data. In detailed design phase, proposed design alternatives are further simulated under site-specific data using SSMs for performance evaluation. LFDSS calculates the required landfill volume, performs landfill base contour design, proposes preliminary design alternatives based on general site conditions, evaluates the performance of the proposed designs, calculates the factor of safety values for slope stability analyses, and performs major cost calculations. The DSS evaluates the results of all landfill design alternatives, and determines whether the design satisfies the predefined performance criteria. The DSS ultimately enables comparisons among different landfill designs based on their performances (i.e. leachate head stability, and groundwater contamination), constructional stability and costs. The developed DSS was applied to a real site, and the results demonstrated the strengths of the developed system on designing environmentally sound and feasible landfills.

  10. Clinical Decision Support for Immunizations (CDSi): A Comprehensive, Collaborative Strategy

    PubMed Central

    Arzt, Noam H.

    2016-01-01

    This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors. PMID:27789956

  11. Database and knowledge base integration in decision support systems.

    PubMed Central

    Johansson, B.; Shahsavar, N.; Ahlfeldt, H.; Wigertz, O.

    1996-01-01

    Since decision support systems (DSS) in medicine often are linked to clinical databases it is important to find methods that facilitate the work for DSS developers to implement database queries in the knowledge base (KB). This paper presents a method for linking clinical databases to a KB with Arden Syntax modules. The method is based on a query meta database including templates for SQL queries. During knowledge module authoring the medical expert only refers to a code in the query meta database. Our method uses standard tools so it can be implemented on different platforms and linked to different clinical databases. PMID:8947666

  12. Knowledge-analytics synergy in Clinical Decision Support.

    PubMed

    Slonim, Noam; Carmeli, Boaz; Goldsteen, Abigail; Keller, Oliver; Kent, Carmel; Rinott, Ruty

    2012-01-01

    Clinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights. Here, we propose the Knowledge-Analytics Synergy paradigm for CDS, in which we synergistically combine existing relevant knowledge with analytics applied to EHR data. We propose a framework for implementing such a paradigm and demonstrate its principles over real-world clinical and genomic data of hypertensive patients.

  13. Use of decision support systems as a drought management tool

    USGS Publications Warehouse

    Frevert, D.; Lins, H.; ,

    2005-01-01

    Droughts present a unique challenge to water managers throughout the world and the current drought in the western United States is taxing facilities to the limit. Coping with this severe drought requires state of the art decision support systems including efficient and accurate hydrologic process models, detailed hydrologic data bases and effective river systems management modeling frameworks. This paper will outline a system of models developed by the Bureau of Reclamation, the US Geological Survey, the University of Colorado and a number of other governmental and university partners. The application of the technology to drought management in several key western river basins will be discussed.

  14. Artificial intelligence based decision support for trumpeter swan management

    USGS Publications Warehouse

    Sojda, Richard S.

    2002-01-01

    The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

  15. Supporting Coral Reef Ecosystem Management Decisions Appropriate to Climate Change

    NASA Astrophysics Data System (ADS)

    Hendee, J. C.; Fletcher, P.; Shein, K. A.

    2013-05-01

    There has been a perception that the myriad of environmental information products derived from satellite and other instrumental sources means ipso facto that there is a direct use for them by environmental managers. Trouble is, as information providers, for the most part we don't really know what decisions managers face daily, nor is it a trivial matter to ascertain the effect of management decisions on the environment, at least in a time frame that facilitates timely maintenance and enhancement of decision support software. To bridge this gap in understanding, we conducted a Needs Assessment (using methodology from the NOAA/Coastal Services Center's Product Design and Evaluation training program) from December, 2011 through May, 2012, in which we queried 15 resource managers in southeast Florida to identify the types of climate data and information products they needed to understand the effects of climate change in their region of purview, and how best these products should be delivered and subsequently enhanced or corrected. Our intent has been to develop a suite of software and information products customized specifically for environmental managers. This report summarizes our success to date, including a report on the development of software for gathering and presenting specific types of climate data, and a narrative about how some U.S. government sponsored efforts, such as Giovanni and TerraVis, as well as non-governmental sponsored efforts such as Marxan, Zonation, SimCLIM, and other off-the-shelf software might be customized for use in specific regions.

  16. Striatal prediction errors support dynamic control of declarative memory decisions

    PubMed Central

    Scimeca, Jason M.; Katzman, Perri L.; Badre, David

    2016-01-01

    Adaptive memory requires context-dependent control over how information is retrieved, evaluated and used to guide action, yet the signals that drive adjustments to memory decisions remain unknown. Here we show that prediction errors (PEs) coded by the striatum support control over memory decisions. Human participants completed a recognition memory test that incorporated biased feedback to influence participants' recognition criterion. Using model-based fMRI, we find that PEs—the deviation between the outcome and expected value of a memory decision—correlate with striatal activity and predict individuals' final criterion. Importantly, the striatal PEs are scaled relative to memory strength rather than the expected trial outcome. Follow-up experiments show that the learned recognition criterion transfers to free recall, and targeting biased feedback to experimentally manipulate the magnitude of PEs influences criterion consistent with PEs scaled relative to memory strength. This provides convergent evidence that declarative memory decisions can be regulated via striatally mediated reinforcement learning signals. PMID:27713407

  17. Decision support system for the operating room rescheduling problem.

    PubMed

    van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J

    2012-12-01

    Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

  18. The approaches for the decision support in case natural hazards

    NASA Astrophysics Data System (ADS)

    Vyazilov, Evgeny; Chunyaev, Nikita

    2013-04-01

    In spite of using highly automated systems of measurement, collecting, storing, handling, prediction and delivery of information on the marine environment, including natural hazards, the amount of damage from natural phenomena increases. Because information on the marine environment delivered to the industrial facilities not effectively used. To such information pays little attention by individual decision-makers and not always perform preventive measures necessary for reduce and prevent damage. Automation of information support will improve the efficiency management of the marine activities. In Russia develops "The Unified system of the information about World ocean" (ESIMO, http://esimo.ru/), that integrates observation, analysis, prognostic and climate data. Necessary to create tools to automatic selection natural disasters through all integrated data; notification decision-makers about arising natural hazards - software agent; provision of information in a compact form for the decision-makers; assessment of possible damage and costs to the preventive measures; providing information on the impacts of environment on economic facilities and recommendations for decision-making; the use of maps, diagrams, tables for reporting. Tools for automatic selection designed for identification of natural phenomena based on the resources ESIMO and corresponding critical values of the indicators environment. The result of this module will be constantly updated database of critical situations of environment for each object or technological process. To operational notify and provide current information about natural hazards proposes using a software agent that is installed on the computer decision-makers, which is activated in case critical situations and provides a minimum of information. In the event of natural disaster software agent should be able to inform decision-makers about this, providing information on the current situation, and the possibility for more and detailed

  19. Critical infrastructure protection decision support system decision model : overview and quick-start user's guide.

    SciTech Connect

    Samsa, M.; Van Kuiken, J.; Jusko, M.; Decision and Information Sciences

    2008-12-01

    The Critical Infrastructure Protection Decision Support System Decision Model (CIPDSS-DM) is a useful tool for comparing the effectiveness of alternative risk-mitigation strategies on the basis of CIPDSS consequence scenarios. The model is designed to assist analysts and policy makers in evaluating and selecting the most effective risk-mitigation strategies, as affected by the importance assigned to various impact measures and the likelihood of an incident. A typical CIPDSS-DM decision map plots the relative preference of alternative risk-mitigation options versus the annual probability of an undesired incident occurring once during the protective life of the investment, assumed to be 20 years. The model also enables other types of comparisons, including a decision map that isolates a selected impact variable and displays the relative preference for the options of interest--parameterized on the basis of the contribution of the isolated variable to total impact, as well as the likelihood of the incident. Satisfaction/regret analysis further assists the analyst or policy maker in evaluating the confidence with which one option can be selected over another.

  20. Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

    PubMed Central

    Arguello Casteleiro, Mercedes; Ainsworth, John; Buchan, Iain

    2015-01-01

    Background Patients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between pathologies, (2) duplication of tests, (3) difficulties in adhering to often conflicting clinical practice guidelines, (4) obstacles in the continuity of care, (5) confusing self-management information, and (6) medication errors. In this context, clinical decision support (CDS) systems need to be able to handle realistic complexity and minimize iatrogenic risks. Objective The aim of this review was to identify to what extent CDS is adopted in multimorbidity. Methods This review followed PRISMA guidance and adopted a multidisciplinary approach. Scopus and PubMed searches were performed by combining terms from 3 different thesauri containing synonyms for (1) multimorbidity and comorbidity, (2) polypharmacy, and (3) CDS. The relevant articles were identified by examining the titles and abstracts. The full text of selected/relevant articles was analyzed in-depth. For articles appropriate for this review, data were collected on clinical tasks, diseases, decision maker, methods, data input context, user interface considerations, and evaluation of effectiveness. Results A total of 50 articles were selected for the full in-depth analysis and 20 studies were included in the final review. Medication (n=10) and clinical guidance (n=8) were the predominant clinical tasks. Four studies focused on merging concurrent clinical practice guidelines. A total of 17 articles reported their CDS systems were knowledge-based. Most articles reviewed considered patients’ clinical records (n=19), clinical practice guidelines (n=12), and clinicians’ knowledge (n=10) as contextual input data. The most frequent diseases mentioned were cardiovascular (n=9) and diabetes mellitus (n=5). In all, 12 articles mentioned generalist doctor(s) as the

  1. Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

    ERIC Educational Resources Information Center

    Campbell, Merle Wayne

    2013-01-01

    Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…

  2. Evaluation of RxNorm for Medication Clinical Decision Support

    PubMed Central

    Freimuth, Robert R.; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G.

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS. PMID:25954360

  3. Towards a decision support system for hand dermatology.

    PubMed

    Mazzola, Luca; Cavazzina, Alice; Pinciroli, Francesco; Bonacina, Stefano; Pigatto, Paolo; Ayala, Fabio; De Pità, Ornella; Marceglia, Sara

    2014-01-01

    The complexity of the medical diagnosis is faced by practitioners relying mainly on their experiences. This can be acquired during daily practices and on-the-job training. Given the complexity and extensiveness of the subject, supporting tools that include knowledge extracted by highly specialized practitioners can be valuable. In the present work, a Decision Support System (DSS) for hand dermatology was developed based on data coming from a Visit Report Form (VRF). Using a Bayesian approach and factors significance difference over the population average for the case, we demonstrated the potentiality of creating an enhanced VRF that include a diagnoses distribution probability based on the DSS rules applied for the specific patient situation. PMID:25160145

  4. Knowledge-based decision support for patient monitoring in cardioanesthesia.

    PubMed

    Schecke, T; Langen, M; Popp, H J; Rau, G; Käsmacher, H; Kalff, G

    1992-01-01

    An approach to generating 'intelligent alarms' is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between 'normal' and 'below normal', are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia. PMID:1402299

  5. Towards sustainable decision-support system facilitating EBM.

    PubMed

    Stolba, Nevena; Nguyen, Tho Manh; Tjoa, A Min

    2007-01-01

    Due to the immense volumes of medical data, the architecture of the future healthcare decision support systems focus more on interoperability than on integration. With the raising need for the creation of unified knowledge base, the federated approach to distributed data warehouses (DWH) is getting increasing attention. In this paper, we explore the idea of a federation technology and its uses within the domain of health, particularly in the conceptualization of DWH federation as a sustainable, appropriate and legitimate solution. Further, we present a federated DWH model which enables the interoperability between heterogeneous and distributed medical IS, which includes a sense and response mechanism and facilitates evidence-based medicine in order to primarily support the physicians at the point of care. A real-world scenario illustrates a possible application field in the area of emergency and intensive care.

  6. Decision Support for Integrated Energy-Water Planning

    NASA Astrophysics Data System (ADS)

    Tidwell, V. C.; William, H.; Klise, G.; Kobos, P. H.; Malczynski, L. A.

    2008-12-01

    Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 40% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. To meet their demand for water, proposed power plants must often target waterways and aquifers prone to overdraft or which may be home to environmentally sensitive species. Acquisition of water rights, permits and public support may therefore be a formidable hurdle when licensing new power plants. Given these current difficulties, what does the future hold when projected growth in population and the economy may require a 30% increase in power generation capacity by 2025? Technology solutions can only take us so far, as noted by the National Energy-Water Roadmap Exercise. This roadmap identified the need for long-term and integrated resource planning supported with scientifically credible models as a leading issue. To address this need a decision support framework is being developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to help identify potential trade-offs, and "best" alternatives among an overwhelming number of energy/water options and objectives. The decision support tool is comprised of three basic elements: a system dynamics model coupling the physical and economic systems important to integrated energy-water planning and management; an optimization toolbox; and a software wrapper that integrates the aforementioned elements along with additional external energy/water models, databases, and visualization products. An interactive interface allows direct interaction with the model and access to real-time results organized according to a variety of reference systems, e.g., from a political, watershed, or electric power grid perspective. With this unique synthesis of various

  7. Integrated Decision Support for Global Environmental Change Adaptation

    NASA Astrophysics Data System (ADS)

    Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

    2011-12-01

    Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this

  8. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values. PMID:26657921

  9. Decision making by urgency gating: theory and experimental support.

    PubMed

    Thura, David; Beauregard-Racine, Julie; Fradet, Charles-William; Cisek, Paul

    2012-12-01

    It is often suggested that decisions are made when accumulated sensory information reaches a fixed accuracy criterion. This is supported by many studies showing a gradual build up of neural activity to a threshold. However, the proposal that this build up is caused by sensory accumulation is challenged by findings that decisions are based on information from a time window much shorter than the build-up process. Here, we propose that in natural conditions where the environment can suddenly change, the policy that maximizes reward rate is to estimate evidence by accumulating only novel information and then compare the result to a decreasing accuracy criterion. We suggest that the brain approximates this policy by multiplying an estimate of sensory evidence with a motor-related urgency signal and that the latter is primarily responsible for neural activity build up. We support this hypothesis using human behavioral data from a modified random-dot motion task in which motion coherence changes during each trial.

  10. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values.

  11. Ontology-based diagnostic decision support in radiology.

    PubMed

    Kahn, Charles E

    2014-01-01

    The Radiology Gamuts Ontology (RGO) is a knowledge model of diseases, interventions, and imaging manifestations. RGO incorporates 16,822 terms with their synonyms and abbreviations and 55,393 relationships between terms. Subsumption defines the relationship between more general and more specific terms; causality relates disorders and their imaging manifestations. We explored the application of the RGO to build an interactive decision support system for radiological diagnosis. The Gamuts DDx system was created to apply the RGO's knowledge: it identifies a list of potential diagnoses in response to one or more user-specified imaging observations. The system also identifies a set of observations that allow one to narrow the diagnosis, and dynamically narrows or expands the list of diagnoses as imaging findings are selected or deselected. The functionality has been implemented as a web-based user interface and as a web service. The current work demonstrates the feasibility of exploiting the RGO's causal knowledge to provide interactive decision support for diagnosis of imaging findings. Ongoing efforts include the further development of the system's knowledge base and evaluation of the system in clinical use. PMID:25160149

  12. How Turing and Wolf influenced my Decision Support Systems.

    PubMed

    Richards, Bernard

    2013-01-01

    Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care.

  13. Ontology-based diagnostic decision support in radiology.

    PubMed

    Kahn, Charles E

    2014-01-01

    The Radiology Gamuts Ontology (RGO) is a knowledge model of diseases, interventions, and imaging manifestations. RGO incorporates 16,822 terms with their synonyms and abbreviations and 55,393 relationships between terms. Subsumption defines the relationship between more general and more specific terms; causality relates disorders and their imaging manifestations. We explored the application of the RGO to build an interactive decision support system for radiological diagnosis. The Gamuts DDx system was created to apply the RGO's knowledge: it identifies a list of potential diagnoses in response to one or more user-specified imaging observations. The system also identifies a set of observations that allow one to narrow the diagnosis, and dynamically narrows or expands the list of diagnoses as imaging findings are selected or deselected. The functionality has been implemented as a web-based user interface and as a web service. The current work demonstrates the feasibility of exploiting the RGO's causal knowledge to provide interactive decision support for diagnosis of imaging findings. Ongoing efforts include the further development of the system's knowledge base and evaluation of the system in clinical use.

  14. How Turing and Wolf influenced my Decision Support Systems.

    PubMed

    Richards, Bernard

    2013-01-01

    Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care. PMID:23542962

  15. Comparing decision-support systems in adopting sustainable intensification criteria

    PubMed Central

    Ahmadi, Bouda Vosough; Moran, Dominic; Barnes, Andrew P.; Baret, Philippe V.

    2015-01-01

    Sustainable intensification (SI) is a multifaceted concept incorporating the ambition to increase or maintain the current level of agricultural yields while reduce negative ecological and environmental impacts. Decision-support systems (DSS) that use integrated analytical methods are often used to support decision making processes in agriculture. However, DSS often consist of set of values, objectives, and assumptions that may be inconsistent or in conflict with merits and objectives of SI. These potential conflicts will have consequences for adoption and up-take of agricultural research, technologies and related policies and regulations such as genetic technology in pursuit of SI. This perspective paper aimed at comparing a number of frequently used socio-economic DSS with respect to their capacity in incorporating various dimensions of SI, and discussing their application to analyzing farm animal genetic resources (FAnGR) policies. The case of FAnGR policies was chosen because of its great potential in delivering merits of SI. It was concluded that flexible DSS, with great integration capacity with various natural and social sciences, are needed to provide guidance on feasibility, practicality, and policy implementation for SI. PMID:25717336

  16. Adoption and sustainability of decision support for patients facing health decisions: an implementation case study in nursing

    PubMed Central

    Stacey, Dawn; Pomey, Marie-Pascale; O'Connor, Annette M; Graham, Ian D

    2006-01-01

    Background Effective interventions prepare patients for making values-sensitive health decisions by helping them become informed and clarifying their values for each of the options. However, patient decision support interventions have not been widely implemented and little is known about effective models for delivering them to patients. The purpose of this study was to describe call centre nurses' adoption of a decision support protocol into practice following exposure to an implementation intervention and to identify factors influencing sustainable nursing practice changes. Methods Exploratory case study at a Canadian province-wide call centre guided by the Ottawa Model of Research Use. Data sources included a survey of nurses who participated in an implementation intervention (n = 31), 2 focus groups with nurses, interviews with 4 administrators, and a document review. Results Twenty-five of 31 nurses responded to the survey measuring adoption of decision support in practice. Of the 25 nurses, 11 had used the decision support protocol in their practice within one month of the intervention. Twenty-two of the 25 intended to use it within the next three months. Although some nurses found it challenging to begin using the protocol, most nurses reported that it: a) helped them recognize callers needing decision support; b) changed their approach to handling these calls; and c) was a positive enhancement to their practice. Strategies identified to promote sustainability of practice changes included integration of the decision support protocol in the call centre database, streamlining the patient decision aids for easier use via telephone, clarifying the administrative direction for the call centre's program, creating a call length guideline specific for these calls, incorporating decision support training in the staff development plan, and informing the public of this enhanced service. Conclusion Although most nurses adopted the decision support protocol for coaching

  17. Traditional versus rule-based programming techniques - Application to the control of optional flight information

    NASA Technical Reports Server (NTRS)

    Ricks, Wendell R.; Abbott, Kathy H.

    1987-01-01

    A traditional programming technique for controlling the display of optional flight information in a civil transport cockpit is compared to a rule-based technique for the same function. This application required complex decision logic and a frequently modified rule base. The techniques are evaluated for execution efficiency and implementation ease; the criterion used to calculate the execution efficiency is the total number of steps required to isolate hypotheses that were true and the criteria used to evaluate the implementability are ease of modification and verification and explanation capability. It is observed that the traditional program is more efficient than the rule-based program; however, the rule-based programming technique is more applicable for improving programmer productivity.

  18. A Methodology to Support Decision Making in Flood Plan Mitigation

    NASA Astrophysics Data System (ADS)

    Biscarini, C.; di Francesco, S.; Manciola, P.

    2009-04-01

    The focus of the present document is on specific decision-making aspects of flood risk analysis. A flood is the result of runoff from rainfall in quantities too great to be confined in the low-water channels of streams. Little can be done to prevent a major flood, but we may be able to minimize damage within the flood plain of the river. This broad definition encompasses many possible mitigation measures. Floodplain management considers the integrated view of all engineering, nonstructural, and administrative measures for managing (minimizing) losses due to flooding on a comprehensive scale. The structural measures are the flood-control facilities designed according to flood characteristics and they include reservoirs, diversions, levees or dikes, and channel modifications. Flood-control measures that modify the damage susceptibility of floodplains are usually referred to as nonstructural measures and may require minor engineering works. On the other hand, those measures designed to modify the damage potential of permanent facilities are called non-structural and allow reducing potential damage during a flood event. Technical information is required to support the tasks of problem definition, plan formulation, and plan evaluation. The specific information needed and the related level of detail are dependent on the nature of the problem, the potential solutions, and the sensitivity of the findings to the basic information. Actions performed to set up and lay out the study are preliminary to the detailed analysis. They include: defining the study scope and detail, the field data collection, a review of previous studies and reports, and the assembly of needed maps and surveys. Risk analysis can be viewed as having many components: risk assessment, risk communication and risk management. Risk assessment comprises an analysis of the technical aspects of the problem, risk communication deals with conveying the information and risk management involves the decision process

  19. Verification and Validation of NASA-Supported Enhancements to Decision Support Tools of PECAD

    NASA Technical Reports Server (NTRS)

    Ross, Kenton W.; McKellip, Rodney; Moore, Roxzana F.; Fendley, Debbie

    2005-01-01

    This section of the evaluation report summarizes the verification and validation (V&V) of recently implemented, NASA-supported enhancements to the decision support tools of the Production Estimates and Crop Assessment Division (PECAD). The implemented enhancements include operationally tailored Moderate Resolution Imaging Spectroradiometer (MODIS) products and products of the Global Reservoir and Lake Monitor (GRLM). The MODIS products are currently made available through two separate decision support tools: the MODIS Image Gallery and the U.S. Department of Agriculture (USDA) Foreign Agricultural Service (FAS) MODIS Normalized Difference Vegetation Index (NDVI) Database. Both the Global Reservoir and Lake Monitor and MODIS Image Gallery provide near-real-time products through PECAD's CropExplorer. This discussion addresses two areas: 1. Assessments of the standard NASA products on which these enhancements are based. 2. Characterizations of the performance of the new operational products.

  20. Aggregation of Environmental Model Data for Decision Support

    NASA Astrophysics Data System (ADS)

    Alpert, J. C.

    2013-12-01

    model output offering access to probability and calibrating information for real time decision making. The aggregation content server reports over ensemble component and forecast time in addition to the other data dimensions of vertical layer and position for each variable. The unpacking, organization and reading of many binary packed files is accomplished most efficiently on the server while weather element event probability calculations, the thresholds for more accurate decision support, or display remain for the client. Our goal is to reduce uncertainty for variables of interest, e.g, agricultural importance. The weather service operational GFS model ensemble and short range ensemble forecasts can make skillful probability forecasts to alert users if and when their selected weather events will occur. A description of how this framework operates and how it can be implemented using existing NOMADS content services and applications is described.

  1. Decision Support: The Keys to Success. AIR 1986 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Oerly, Diane

    Characteristics of a decision support system (DSS) and factors that influence system design are described, along with a decision support database at the University of Missouri-Columbia. Reasons that the institutional research office is in a unique position to support decision-making are identified. A review of the literature of DSS briefly covers…

  2. Making Risk Models Operational for Situational Awareness and Decision Support

    SciTech Connect

    Paulson, Patrick R.; Coles, Garill A.; Shoemaker, Steven V.

    2012-06-12

    Modernization of nuclear power operations control systems, in particular the move to digital control systems, creates an opportunity to modernize existing legacy infrastructure and extend plant life. We describe here decision support tools that allow the assessment of different facets of risk and support the optimization of available resources to reduce risk as plants are upgraded and maintained. This methodology could become an integrated part of the design review process and a part of the operations management systems. The methodology can be applied to the design of new reactors such as small nuclear reactors (SMR), and be helpful in assessing the risks of different configurations of the reactors. Our tool provides a low cost evaluation of alternative configurations and provides an expanded safety analysis by considering scenarios while early in the implementation cycle where cost impacts can be minimized. The effects of failures can be modeled and thoroughly vetted to understand their potential impact on risk. The process and tools presented here allow for an integrated assessment of risk by supporting traditional defense in depth approaches while taking into consideration the insertion of new digital instrument and control systems.

  3. Clinical decision support for perioperative information management systems.

    PubMed

    Wanderer, Jonathan P; Ehrenfeld, Jesse M

    2013-12-01

    Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered.

  4. 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.

  5. Mining multi-dimensional data for decision support

    SciTech Connect

    Donato, J.M.; Schryver, J.C.; Hinkel, G.C.; Schmoyer, R.L. Jr.; Grady, N.W.; Leuze, M.R. |

    1998-06-01

    While it is widely recognized that data can be a valuable resource for any organization, extracting information contained within the data is often a difficult problem. Attempts to obtain information from data may be limited by legacy data storage formats, lack of expert knowledge about the data, difficulty in viewing the data, or the volume of data needing to be processed. The rapidly developing field of Data Mining or Knowledge Data Discovery is a blending of Artificial Intelligence, Statistics, and Human-Computer Interaction. Sophisticated data navigation tools to obtain the information needed for decision support do not yet exist. Each data mining task requires a custom solution that depends upon the character and quantity of the data. This paper presents a two-stage approach for handling the prediction of personal bankruptcy using credit card account data, combining decision tree and artificial neural network technologies. Topics to be discussed include the pre-processing of data, including data cleansing, the filtering of data for pertinent records, and the reduction of data for attributes contributing to the prediction of bankruptcy, and the two steps in the mining process itself.

  6. Query-handling in MLM-based decision support systems.

    PubMed

    Arkad, K; Gao, X M; Ahlfeldt, H

    1995-01-01

    Arden Syntax for Medical Logic Modules is a standard specification for creation and sharing of knowledge bases. The standard specification focuses on knowledge that can be represented as a set of independent Medical Logic Modules (MLMs) such as rules, formulas and protocols. The basic functions of an MLM are to retrieve patient data, manipulate the data, come to some decision, and possibly perform an action. All connections to the world outside an MLM are collected in the data-slot of the MLM. The institution specific parts of these connections are inside the notation of curly brackets ([]) to facilitate sharing of MLM between institutions. This paper focuses on some of the problems that occur in relation to Arden Syntax and connections to a patient database such as database queries. Problems related to possibilities of moving one or several module(s) are also discussed, with emphasis on database connections. As an example, an MLM based Decision Support System (DSS) developed at Linköping University is described. PMID:8882561

  7. Seasonal Stream Flow Forecasting and Decision Support in Central Texas

    NASA Astrophysics Data System (ADS)

    Watkins, D. W.; Nykanen, D. K.; Mahmoud, M.; Wei, W.

    2003-12-01

    A decision support model based on stream flow ensemble forecasts has been developed for the Lower Colorado River Authority in Central Texas, and predictive skill is added to climatology-based forecasts by conditioning the ensembles on observable climate indicators. These indicators include stream flow (persistence), soil moisture, and large-scale recurrent patterns such as the El Nino-Southern Oscillation, Pacific Decadal Oscillation, and the North Atlantic Oscillation. In the absence of historical soil moisture measurements, the Variable Infiltration Capacity (VIC) Retrospective Land Surface Data Set is applied. Strong correlation between observed runoff volumes and runoff volumes simulated by the (uncalibrated) VIC model indicates the viability of this approach. Following correlation analysis to screen potential predictors, a Bayesian procedure for updating ensemble probabilities is outlined, and various skill scores are reviewed for evaluating forecast performance. Verification of the ensemble forecasts using a resampling procedure indicates a small but potentially significant improvement in forecast skill over climatology that could be exploited in seasonal water management decisions. Future work involves evaluation of seasonal soil moisture forecasts, further evaluation of annual flow forecasts, incorporation of climate forecasts in reservoir operating rules, and estimation of the value of the forecasts.

  8. Decision Support for Iteration Scheduling in Agile Environments

    NASA Astrophysics Data System (ADS)

    Szőke, Ákos

    Today’s software business development projects often lay claim to low-risk value to the customers in order to be financed. Emerging agile processes offer shorter investment periods, faster time-to-market and better customer satisfaction. To date, however, in agile environments there is no sound methodological schedule support contrary to the traditional plan-based approaches. To address this situation, we present an agile iteration scheduling method whose usefulness is evaluated with post-mortem simulation. It demonstrates that the method can significantly improve load balancing of resources (cca. 5×), produce higher quality and lower-risk feasible schedule, and provide more informed and established decisions by optimized schedule production. Finally, the paper analyzes benefits and issues from the use of this method.

  9. Impact Decision Support Services in the Arctic - A Case Study

    NASA Astrophysics Data System (ADS)

    Scott, C. A.

    2015-12-01

    The National Weather Service Alaska Region's (AR) Regional Operation Center (ROC) provided weather and ice decision support services for the Bureau of Ocean and Energy Management (BOEM) oversight of Royal Dutch Shell's exploratory drilling operations in the Chukchi Sea during the summer and early fall of 2015. The AR ROC, coordinated input from WFO's Anchorage and Fairbanks, the NCEP/Ocean Prediction Center and Climate Prediction Center, and NOAA's National Ice Center. Briefings began in early Spring 2015, focused on melt-out and freeze up dates in the vicinity of the "Burger" drill site. Initially packages were prepared and briefed twice weekly. The frequency increased as the drilling season progressed, and included marine and aviation weather forecasts, current and forecast sea ice conditions as it impacts vessels and aircraft transiting to and from the drilling sites in the Chukchi Sea. Spot forecasts are also available for specific missions as needed.

  10. Spatio-temporal Visualization for Environmental Decision Support

    SciTech Connect

    Bhaduri, Budhendra L.; Shankar, Mallikarjun; Sorokine, Alexandre; Ganguly, Auroop R.

    2009-01-01

    Traditional visualization of earth surface features has been addressed through visual exploration, analysis, synthesis, and presentation of observable geospatial data. However, characterizing the changes in their observable and unobservable properties of geospatial features is critical for planning and policy formulation. Recent approaches are addressing modeling and visualization of the temporal dynamics that describe observed and/or predicted physical and socioeconomic processes using vast volumes of earth observation (imagery and other geophysical) data from remote sensor networks. This paper provides an overview of selected geospatial modeling and simulation, exploratory analysis of earth observation data, and high performance visualization research at Oak Ridge National Laboratory for developing novel data driven approaches for geospatial knowledge discovery and visualization relevant to environmental decision support.

  11. Intelligent decision support technologies for design and manufacturing

    SciTech Connect

    Zacharia, T.; Allen, J.D.; Ivezic, N.; Ludtka, G.M.

    1997-06-01

    For many of today`s complex manufacturing processes, there exists a solid body of knowledge that enables direct simulations of such processes yielding predictions about the final product and process characteristics using finite element or finite difference methods. However, the computational complexities of these simulations are such that they do not lend themselves easily to routine and timely use in optimization and control of manufacturing processes. More recently, neural network-based decision support technologies have been developed which hold the promise of bringing the body of analytical and simulation knowledge closer to the design and optimization processes in manufacturing industries. The paper discusses the application of a holistic approach wherein existing finite element, neural-network, and optical metrology methods are combined to develop a real time tool for optimization and control of the sheet metal stamping process. Significant issues in the development of such a tool and results from its application to a deformation process are discussed.

  12. Protective jacket enabling decision support for workers in cold climate.

    PubMed

    Seeberg, Trine M; Vardoy, Astrid-Sofie B; Austad, Hanne O; Wiggen, Oystein; Stenersen, Henning S; Liverud, Anders E; Storholmen, Tore Christian B; Faerevik, Hilde

    2013-01-01

    The cold and harsh climate in the High North represents a threat to safety and work performance. The aim of this study was to show that sensors integrated in clothing can provide information that can improve decision support for workers in cold climate without disturbing the user. Here, a wireless demonstrator consisting of a working jacket with integrated temperature, humidity and activity sensors has been developed. Preliminary results indicate that the demonstrator can provide easy accessible information about the thermal conditions at the site of the worker and local cooling effects of extremities. The demonstrator has the ability to distinguish between activity and rest, and enables implementation of more sophisticated sensor fusion algorithms to assess work load and pre-defined activities. This information can be used in an enhanced safety perspective as an improved tool to advice outdoor work control for workers in cold climate.

  13. A Framework for Decision Support Systems Based on Zachman Framework

    NASA Astrophysics Data System (ADS)

    Ostadzadeh, S. Shervin; Habibi, Jafar; Ostadzadeh, S. Arash

    Recent challenges have brought about an inevitable tendency for enterprises to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of information systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have critical roles in enterprise management and system development. In this paper, we propose a framework based on ZF for Decision Support Systems (DSS). Furthermore, a modeling approach based on Model-Driven Architecture (MDA) is utilized to obtain compatible models for all cells in the framework. The efficiency of the proposed framework is examined through a case study.

  14. Clinical Decision Support for Early Recognition of Sepsis.

    PubMed

    Amland, Robert C; Hahn-Cover, Kristin E

    2016-01-01

    Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient's infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours. PMID:25385815

  15. Clinical Decision Support Knowledge Management: Strategies for Success.

    PubMed

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

  16. NOAA Climate Information and Tools for Decision Support Services

    NASA Astrophysics Data System (ADS)

    Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

    2013-12-01

    NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to

  17. Clinical Decision Support for Colon and Rectal Surgery: An Overview

    PubMed Central

    McCoy, Allison B.; Melton, Genevieve B.; Wright, Adam; Sittig, Dean F.

    2013-01-01

    Clinical decision support (CDS) has been shown to improve clinical processes, promote patient safety, and reduce costs in healthcare settings, and it is now a requirement for clinicians as part of the Meaningful Use Regulation. However, most evidence for CDS has been evaluated primarily in internal medicine care settings, and colon and rectal surgery (CRS) has unique needs with CDS that are not frequently described in the literature. The authors reviewed published literature in informatics and medical journals, combined with expert opinion to define CDS, describe the evidence for CDS, outline the implementation process for CDS, and present applications of CDS in CRS.CDS functionalities such as order sets, documentation templates, and order facilitation aids are most often described in the literature and most likely to be beneficial in CRS. Further research is necessary to identify and better evaluate additional CDS systems in the setting of CRS. PMID:24436644

  18. Clinical Decision Support Knowledge Management: Strategies for Success.

    PubMed

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital. PMID:26152955

  19. Examining the Relationship between Clinical Decision Support and Performance Measurement

    PubMed Central

    Haggstrom, David A.; Saleem, Jason J.; Militello, Laura G.; Arbuckle, Nicole; Flanagan, Mindy; Doebbeling, Bradley N.

    2009-01-01

    In concept and practice, clinical decision support (CDS) and performance measurement represent distinct approaches to organizational change, yet these two organizational processes are interrelated. We set out to better understand how the relationship between the two is perceived, as well as how they jointly influence clinical practice. To understand the use of CDS at benchmark institutions, we conducted semistructured interviews with key managers, information technology personnel, and clinical leaders during a qualitative field study. Improved performance was frequently cited as a rationale for the use of clinical reminders. Pay-for-performance efforts also appeared to provide motivation for the use of clinical reminders. Shared performance measures were associated with shared clinical reminders. The close link between clinical reminders and performance measurement causes these tools to have many of the same implementation challenges. PMID:20351854

  20. PATHway: Decision Support in Exercise Programmes for Cardiac Rehabilitation.

    PubMed

    Filos, Dimitris; Triantafyllidis, Andreas; Chouvarda, Ioanna; Buys, Roselien; Cornelissen, Véronique; Budts, Werner; Walsh, Deirdre; Woods, Catherine; Moran, Kieran; Maglaveras, Nicos

    2016-01-01

    Rehabilitation is important for patients with cardiovascular diseases (CVD) to improve health outcomes and quality of life. However, adherence to current exercise programmes in cardiac rehabilitation is limited. We present the design and development of a Decision Support System (DSS) for telerehabilitation, aiming to enhance exercise programmes for CVD patients through ensuring their safety, personalising the programme according to their needs and performance, and motivating them toward meeting their physical activity goals. The DSS processes data originated from a Microsoft Kinect camera, a blood pressure monitor, a heart rate sensor and questionnaires, in order to generate a highly individualised exercise programme and improve patient adherence. Initial results within the EU-funded PATHway project show the potential of our approach.

  1. The role of informatics and decision support in utilization management.

    PubMed

    Baron, Jason M; Dighe, Anand S

    2014-01-01

    Information systems provide a critical link between clinical laboratories and the clinicians and patients they serve. Strategic deployment of informatics resources can enable a wide array of utilization initiatives and can substantially improve the appropriateness of test selection and results interpretation. In this article, we review information systems including computerized provider order entry (CPOE) systems, laboratory information systems (LISs), electronic health records (EHRs), laboratory middleware, knowledge management systems and systems for data extraction and analysis, and describe the role that each can play in utilization management. We also discuss specific utilization strategies that laboratories can employ within these systems, citing examples both from our own institution and from the literature. Finally, we review how emerging applications of decision support technologies may help to further refine test utilization, "personalize" laboratory diagnosis, and enhance the diagnostic value of laboratory testing.

  2. Decision support systems and methods for complex networks

    DOEpatents

    Huang, Zhenyu; Wong, Pak Chung; Ma, Jian; Mackey, Patrick S; Chen, Yousu; Schneider, Kevin P

    2012-02-28

    Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

  3. Patterns of use of decision support tools by clinicians.

    PubMed

    Hayward, Robert S; El-Hajj, Mohamad; Voth, Tanya K; Deis, Kelly

    2006-01-01

    This paper analyses information behavior data automatically gathered by an integrated clinical information environment used by internal medicine physicians and trainees at the University of Alberta. The study reviews how clinical information systems, decision-support tools and evidence resources were used over a 13 month period. Aggregate and application-specific frequency and duration of use was compared for location, time of day, physician status, and application-type (clinical information system or 5 categories of knowledge resources). Significant differences are observed for when and where resources were used, diurnal patterns of use, minutes spent per encounter, and patterns of use for physicians and trainees. We find that evidence use is not restricted to either the place or time of clinical work, resources are used for very short periods at the point-of-care, and that use of filtered evidence-based resources is concentrated among trainees.

  4. Protective jacket enabling decision support for workers in cold climate.

    PubMed

    Seeberg, Trine M; Vardoy, Astrid-Sofie B; Austad, Hanne O; Wiggen, Oystein; Stenersen, Henning S; Liverud, Anders E; Storholmen, Tore Christian B; Faerevik, Hilde

    2013-01-01

    The cold and harsh climate in the High North represents a threat to safety and work performance. The aim of this study was to show that sensors integrated in clothing can provide information that can improve decision support for workers in cold climate without disturbing the user. Here, a wireless demonstrator consisting of a working jacket with integrated temperature, humidity and activity sensors has been developed. Preliminary results indicate that the demonstrator can provide easy accessible information about the thermal conditions at the site of the worker and local cooling effects of extremities. The demonstrator has the ability to distinguish between activity and rest, and enables implementation of more sophisticated sensor fusion algorithms to assess work load and pre-defined activities. This information can be used in an enhanced safety perspective as an improved tool to advice outdoor work control for workers in cold climate. PMID:24111230

  5. A Clinical Decision Support System for Breast Cancer Patients

    NASA Astrophysics Data System (ADS)

    Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

    This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

  6. SERVIR: A Regional Monitoring and Decision Support System for Mesoamerica

    NASA Astrophysics Data System (ADS)

    Irwin, D.; Hardin, D. M.; Sever, T.; Graves, S.

    2008-05-01

    Mesoamerica is a prime example of a multi-national region with natural and human induced stresses that benefits from information provided by observation systems. The region is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability of its population to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, the University of Alabama in Huntsville and numerous SERVIR* partners are developing data products, knowledge extraction methods and decision support tools for environmental monitoring, disaster response and sustainable growth planning in Mesoamerica. The combination of space- based observations from NASA's Earth Observing Satellites with information management and knowledge extraction technologies has yielded a robust system for use by scientists, educators, environmental ministers and policy makers. These resources enhance the ability to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. Now in its fourth year SERVIR has become a partner in the International Space and Major Disasters Charter. In the past year the Charter provided commercial satellite imagery to aid in disaster response to Hurricanes Dean, Felix and Noel. Overcoming roadblocks to coordination and data sharing between countries, organizations and disciplines SERVIR is providing environmental monitoring and decision support products and applications that directly map to several Observation GEOSS societal benefit areas. This paper provides an overview of the ongoing accomplishments of the SERVIR project. *SERVIR is a Spanish verb meaning "to serve" or "be useful" is also an acronym for the Spanish name of the capability: Sistema Regional de Visualizacion y Monitero.

  7. Facilitating knowledge transfer: decision support tools in environment and health.

    PubMed

    Liu, Hai-Ying; Bartonova, Alena; Neofytou, Panagiotis; Yang, Aileen; Kobernus, Michael J; Negrenti, Emanuele; Housiadas, Christos

    2012-01-01

    The HENVINET Health and Environment Network aimed to enhance the use of scientific knowledge in environmental health for policy making. One of the goals was to identify and evaluate Decision Support Tools (DST) in current use. Special attention was paid to four "priority" health issues: asthma and allergies, cancer, neurodevelopment disorders, and endocrine disruptors.We identified a variety of tools that are used for decision making at various levels and by various stakeholders. We developed a common framework for information acquisition about DSTs, translated this to a database structure and collected the information in an online Metadata Base (MDB).The primary product is an open access web-based MDB currently filled with 67 DSTs, accessible through the HENVINET networking portal http://www.henvinet.eu and http://henvinet.nilu.no. Quality assurance and control of the entries and evaluation of requirements to use the DSTs were also a focus of the work. The HENVINET DST MDB is an open product that enables the public to get basic information about the DSTs, and to search the DSTs using pre-designed attributes or free text. Registered users are able to 1) review and comment on existing DSTs; 2) evaluate each DST's functionalities, and 3) add new DSTs, or change the entry for their own DSTs. Assessment of the available 67 DSTs showed: 1) more than 25% of the DSTs address only one pollution source; 2) 25% of the DSTs address only one environmental stressor; 3) almost 50% of the DSTs are only applied to one disease; 4) 41% of the DSTs can only be applied to one decision making area; 5) 60% of the DSTs' results are used only by national authority and/or municipality/urban level administration; 6) almost half of the DSTs are used only by environmental professionals and researchers. This indicates that there is a need to develop DSTs covering an increasing number of pollution sources, environmental stressors and health end points, and considering links to other 'Driving

  8. Observations to support adaptation: Principles, scales and decision-making

    NASA Astrophysics Data System (ADS)

    Pulwarty, R. S.

    2012-12-01

    As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks

  9. Exploration Clinical Decision Support System: Medical Data Architecture

    NASA Technical Reports Server (NTRS)

    Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)

    2016-01-01

    The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear

  10. WEB-GIS Decision Support System for CO2 storage

    NASA Astrophysics Data System (ADS)

    Gaitanaru, Dragos; Leonard, Anghel; Radu Gogu, Constantin; Le Guen, Yvi; Scradeanu, Daniel; Pagnejer, Mihaela

    2013-04-01

    Environmental decision support systems (DSS) paradigm evolves and changes as more knowledge and technology become available to the environmental community. Geographic Information Systems (GIS) can be used to extract, assess and disseminate some types of information, which are otherwise difficult to access by traditional methods. In the same time, with the help of the Internet and accompanying tools, creating and publishing online interactive maps has become easier and rich with options. The Decision Support System (MDSS) developed for the MUSTANG (A MUltiple Space and Time scale Approach for the quaNtification of deep saline formations for CO2 storaGe) project is a user friendly web based application that uses the GIS capabilities. MDSS can be exploited by the experts for CO2 injection and storage in deep saline aquifers. The main objective of the MDSS is to help the experts to take decisions based large structured types of data and information. In order to achieve this objective the MDSS has a geospatial objected-orientated database structure for a wide variety of data and information. The entire application is based on several principles leading to a series of capabilities and specific characteristics: (i) Open-Source - the entire platform (MDSS) is based on open-source technologies - (1) database engine, (2) application server, (3) geospatial server, (4) user interfaces, (5) add-ons, etc. (ii) Multiple database connections - MDSS is capable to connect to different databases that are located on different server machines. (iii)Desktop user experience - MDSS architecture and design follows the structure of a desktop software. (iv)Communication - the server side and the desktop are bound together by series functions that allows the user to upload, use, modify and download data within the application. The architecture of the system involves one database and a modular application composed by: (1) a visualization module, (2) an analysis module, (3) a guidelines module

  11. Improvements in agricultural water decision support using remote sensing

    NASA Astrophysics Data System (ADS)

    Marshall, M. T.

    2012-12-01

    Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of

  12. FRAMEWORK FOR DECISION SUPPORT USED IN CONTAMINATED LAND MANAGEMENT IN EUROPE AND NORTH AMERICA.

    SciTech Connect

    SULLIVAN,T.; BARDOS,R.P.; MAROT,C.; MARIOTTI,R.

    2000-06-01

    Effective contaminated land management requires a number of decisions addressing a suite of technical, economic and social concerns. This paper offers a common framework and terminology for describing decision support approaches, along with an overview of recent applications of decision support tools in Europe and the USA. A common problem with work on decision support approaches is a lack of a common framework and terminology to describe the process. These have been proposed in this paper.

  13. Using Google Earth in Marine Research and Operational Decision Support

    NASA Astrophysics Data System (ADS)

    Blower, J. D.; Bretherton, D.; Haines, K.; Liu, C.; Rawlings, C.; Santokhee, A.; Smith, I.

    2006-12-01

    A key advantage of Virtual Globes ("geobrowsers") such as Google Earth is that they can display many different geospatial data types at a huge range of spatial scales. In this demonstration and poster display we shall show how marine data from disparate sources can be brought together in a geobrowser in order to support both scientific research and operational search and rescue activities. We have developed the Godiva2 interactive website for browsing and exploring marine data, mainly output from supercomputer analyses and predictions of ocean circulation. The user chooses a number of parameters (e.g. sea temperature at 100m depth on 1st July 2006) and can load an image of the resulting data in Google Earth. Through the use of an automatically-refreshing NetworkLink the user can explore the whole globe at a very large range of spatial scales: the displayed data will automatically be refreshed to show data at increasingly fine resolution as the user zooms in. This is a valuable research tool for exploring these terabyte- scale datasets. Many coastguard organizations around the world use SARIS, a software application produced by BMT Cordah Ltd., to predict the drift pattern of objects in the sea in order to support search and rescue operations. Different drifting objects have different trajectories depending on factors such as their buoyancy and windage and so a computer model, supported by meteorological and oceanographic data, is needed to help rescuers locate their targets. We shall demonstrate how Google Earth is used to display output from the SARIS model (including the search target location and associated error polygon) alongside meteorological data (wind vectors) and oceanographic data (sea temperature, surface currents) from Godiva2 in order to support decision-making. We shall also discuss the limitations of using Google Earth in this context: these include the difficulties of working with time- dependent data and the need to access data securely. essc

  14. Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

    PubMed

    Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

    2009-04-01

    Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

  15. A critical assessment of supported decision-making for persons aging with intellectual disabilities.

    PubMed

    Kohn, Nina A; Blumenthal, Jeremy A

    2014-01-01

    Supported decision-making is increasingly being promoted as an alternative to guardianship for persons aging with intellectual disabilities. Proponents argue that supported decision-making, unlike guardianship, empowers persons with disabilities by providing them with help in making their own decisions, rather than simply providing someone else to make decisions for them. To evaluate the empirical support for these claims, we reviewed the evidence base on supported decision-making. Our review found little such empirical research, suggesting that significant further research is warranted to determine whether--and under what conditions--supported decision-making can benefit persons with intellectual disabilities. Indeed, without more empirical evidence as to how supported decision-making functions in practice, it is too early to rule out the possibility it may actually disempower individuals with disabilities by facilitating undue influence by their alleged supporters. We therefore suggest several key areas for future research.

  16. Verification and Validation of NASA-Supported Enhancements to PECAD's Decision Support Tools

    NASA Technical Reports Server (NTRS)

    McKellipo, Rodney; Ross, Kenton W.

    2006-01-01

    The NASA Applied Sciences Directorate (ASD), part of the Earth-Sun System Division of NASA's Science Mission Directorate, has partnered with the U.S. Department of Agriculture (USDA) to enhance decision support in the area of agricultural efficiency-an application of national importance. The ASD integrated the results of NASA Earth science research into USDA decision support tools employed by the USDA Foreign Agricultural Service (FAS) Production Estimates and Crop Assessment Division (PECAD), which supports national decision making by gathering, analyzing, and disseminating global crop intelligence. Verification and validation of the following enhancements are summarized: 1) Near-real-time Moderate Resolution Imaging Spectroradiometer (MODIS) products through PECAD's MODIS Image Gallery; 2) MODIS Normalized Difference Vegetation Index (NDVI) time series data through the USDA-FAS MODIS NDVI Database; and 3) Jason-1 and TOPEX/Poseidon lake level estimates through PECAD's Global Reservoir and Lake Monitor. Where possible, each enhanced product was characterized for accuracy, timeliness, and coverage, and the characterized performance was compared to PECAD operational requirements. The MODIS Image Gallery and the GRLM are more mature and have achieved a semi-operational status, whereas the USDA-FAS MODIS NDVI Database is still evolving and should be considered

  17. Creating a GIS-Based Decision-Support System

    NASA Technical Reports Server (NTRS)

    Alvarado, Lori; Gates, Ann Q.; Gray, Bob; Reyes, Raul

    1998-01-01

    Tilting the Balance: Climate Variability and Water Resource Management in the Southwest, a regional conference hosted by the Pan American Center for Environmental Studies, will be held at The University of Texas at El Paso on March 2-4, 1998. The conference is supported through the US Global Change Research Program (USGCRP) established by the President in 1989, and codified by Congress in the Global Change Research Act of 1990. The NASA Mission to Planet Earth program is one of the workshops sponsors. The purpose of the regional workshops is to improve understanding of the consequences of global change. This workshop will be focused on issues along the border and the Rio Grande River and thus will bring together stakeholders from Mexico, California, Texas, New Mexico, Arizona and Colorado representing federal, state, and local governments; universities and laboratories; industry, agricultural and natural resource managers; and non-governmental organizations. This paper discusses the efforts of the NASA PACES center create a GIS-based decision-support system that can be used to facilitate discussion of the complex issues of resource management within the targeted international region.

  18. Object-oriented design and programming in medical decision support.

    PubMed

    Heathfield, H; Armstrong, J; Kirkham, N

    1991-12-01

    The concept of object-oriented design and programming has recently received a great deal of attention from the software engineering community. This paper highlights the realisable benefits of using the object-oriented approach in the design and development of clinical decision support systems. These systems seek to build a computational model of some problem domain and therefore tend to be exploratory in nature. Conventional procedural design techniques do not support either the process of model building or rapid prototyping. The central concepts of the object-oriented paradigm are introduced, namely encapsulation, inheritance and polymorphism, and their use illustrated in a case study, taken from the domain of breast histopathology. In particular, the dual roles of inheritance in object-oriented programming are examined, i.e., inheritance as a conceptual modelling tool and inheritance as a code reuse mechanism. It is argued that the use of the former is not entirely intuitive and may be difficult to incorporate into the design process. However, inheritance as a means of optimising code reuse offers substantial technical benefits.

  19. Decision support system for managing oil spill events.

    PubMed

    Keramitsoglou, Iphigenia; Cartalis, Constantinos; Kassomenos, Pavlos

    2003-08-01

    The Mediterranean environment is exposed to various hazards, including oil spills, forest fires, and floods, making the development of a decision support system (DSS) for emergency management an objective of utmost importance. The present work presents a complete DSS for managing marine pollution events caused by oil spills. The system provides all the necessary tools for early detection of oil-spills from satellite images, monitoring of their evolution, estimation of the accident consequences and provision of support to responsible Public Authorities during clean-up operations. The heart of the system is an image processing-geographic information system and other assistant individual software tools that perform oil spill evolution simulation and all other necessary numerical calculations as well as cartographic and reporting tasks related to a specific management of the oil spill event. The cartographic information is derived from the extant general maps representing detailed information concerning several regional environmental and land-cover characteristics as well as financial activities of the application area. Early notification of the authorities with up-to-date accurate information on the position and evolution of the oil spill, combined with the detailed coastal maps, is of paramount importance for emergency assessment and effective clean-up operations that would prevent environmental hazard. An application was developed for the Region of Crete, an area particularly vulnerable to oil spills due to its location, ecological characteristics, and local economic activities.

  20. Documentation of a decision framework to support enhanced sludge washing

    SciTech Connect

    Brothers, A.J.

    1995-12-31

    This document describes a proposed decision model that, if developed to its fullest, can provide a wide range of analysis options and insights to pretreatment/sludge washing alternatives. A recent decision has been made to terminate this work

  1. Developing a Software for Fuzzy Group Decision Support System: A Case Study

    ERIC Educational Resources Information Center

    Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem

    2009-01-01

    The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…

  2. Research on web-based decision support system for sports competitions

    NASA Astrophysics Data System (ADS)

    Huo, Hanqiang

    2010-07-01

    This paper describes the system architecture and implementation technology of the decision support system for sports competitions, discusses the design of decision-making modules, management modules and security of the system, and proposes the development idea of building a web-based decision support system for sports competitions.

  3. NWS Alaska Sea Ice Program: Operations and Decision Support Services

    NASA Astrophysics Data System (ADS)

    Schreck, M. B.; Nelson, J. A., Jr.; Heim, R.

    2015-12-01

    The National Weather Service's Alaska Sea Ice Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska Sea Ice Program offers daily sea ice and sea surface temperature analysis products. The program also delivers a five day sea ice forecast 3 times each week, provides a 3 month sea ice outlook at the end of each month, and has staff available to respond to sea ice related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer sea ice free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska Sea Ice Program. The ASIP is in constant contact with the National Ice Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on sea ice outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska Sea Ice Program as well as delve into what we see as the future of the ASIP.

  4. Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

    NASA Technical Reports Server (NTRS)

    Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

    2013-01-01

    Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

  5. Future of medical knowledge management and decision support.

    PubMed

    Greenes, Robert A

    2002-01-01

    Attempts to predict the future are typically off the mark. Beyond the challenges of forecasting the stock market or the weather, dramatic instances of notoriously inaccurate prognostications have been those by the US patent office in the late 1800s about the future of inventions, by Thomas Watson in the 1930s about the market for large computers, and by Bill Gates in the early 1990s about the significance of the Internet. When one seeks to make predictions about health care, one finds that, beyond the usual uncertainties regarding the future, additional impediments to forecasting are the discontinuities introduced by advances in biomedical science and technology, the impact of information technology, and the reorganizations and realignments attending various approaches to health care delivery and finance. Changes in all three contributing areas themselves can be measured in "PSPYs", or paradigm shifts per year. Despite these risks in forecasting, I believe that certain trends are sufficiently clear that I am willing to venture a few predictions. Further, the predictions I wish to make suggest a goal for the future that can be achieved, if we can align the prevailing political, financial, biomedical, and technical forces toward that end. Thus, in a sense this is a call to action, to shape the future rather than just let it happen. This chapter seeks to lay out the direction we are heading in knowledge management and decision support, and to delineate an information technology framework that appears desirable. I believe the framework to be discussed is of importance to the health care-related knowledge management and decision making activities of the consumer and patient, the health care provider, and health care delivery organizations and insurers. The approach is also relevant to the other dimensions of academic health care institution activities, notably the conduct of research and the processes of education and learning. PMID:12026135

  6. Information Systems to Support a Decision Process at Stanford.

    ERIC Educational Resources Information Center

    Chaffee, Ellen Earle

    1982-01-01

    When a rational decision process is desired, information specialists can contribute information and also contribute to the process in which that information is used, thereby promoting rational decision-making. The contribution of Stanford's information specialists to rational decision-making is described. (MLW)

  7. An architecture for rule based system explanation

    NASA Technical Reports Server (NTRS)

    Fennel, T. R.; Johannes, James D.

    1990-01-01

    A system architecture is presented which incorporate both graphics and text into explanations provided by rule based expert systems. This architecture facilitates explanation of the knowledge base content, the control strategies employed by the system, and the conclusions made by the system. The suggested approach combines hypermedia and inference engine capabilities. Advantages include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. User models are suggested to control the type, amount, and order of information presented.

  8. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    NASA Astrophysics Data System (ADS)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  9. Is there a need for hydrological modelling in decision support systems for nuclear emergencies.

    PubMed

    Raskob, W; Heling, R; Zheleznyak, M

    2004-01-01

    This paper discusses the role of hydrological modelling in decision support systems for nuclear emergencies. In particular, most recent developments such as, the radionuclide transport models integrated in to the decision support system RODOS will be explored. Recent progress in the implementation of physically-based distributed hydrological models for operational forecasting in national and supranational centres, may support a closer cooperation between national hydrological services and therefore, strengthen the use of hydrological and radiological models implemented in decision support systems.

  10. Visualization Component of Vehicle Health Decision Support System

    NASA Technical Reports Server (NTRS)

    Jacob, Joseph; Turmon, Michael; Stough, Timothy; Siegel, Herbert; Walter, patrick; Kurt, Cindy

    2008-01-01

    The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a

  11. Towards a Decision Support System for Space Flight Operations

    NASA Technical Reports Server (NTRS)

    Meshkat, Leila; Hogle, Charles; Ruszkowski, James

    2013-01-01

    The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of

  12. Decentralizing Data through Decision-Support Systems: The Impact of Increased Access to Data on Decision Making

    ERIC Educational Resources Information Center

    Petrides, Lisa A.; McClelland, Sara I.

    2007-01-01

    This study examines the impact of a new Decision-Support System (DSS) on decision making in a community college in California. It looks at how attitudes and behaviors about data and their use were impacted by the implementation of a new DSS. The study found that the decentralization of data, through the DSS, produced a shift in terms of an…

  13. Generalized Tumor Dose for Treatment Planning Decision Support

    NASA Astrophysics Data System (ADS)

    Zuniga, Areli A.

    Modern radiation therapy techniques allow for improved target conformity and normal tissue sparing. These highly conformal treatment plans have allowed dose escalation techniques increasing the probability of tumor control. At the same time this conformation has introduced inhomogeneous dose distributions, making delivered dose characterizations more difficult. The concept of equivalent uniform dose (EUD) characterizes a heterogeneous dose distribution within irradiated structures as a single value and has been used in biologically based treatment planning (BBTP); however, there are no substantial validation studies on clinical outcome data supporting EUD's use and therefore has not been widely adopted as decision-making support. These highly conformal treatment plans have also introduced the need for safety margins around the target volume. These margins are designed to minimize geometrical misses, and to compensate for dosimetric and treatment delivery uncertainties. The margin's purpose is to reduce the chance of tumor recurrence. This dissertation introduces a new EUD formulation designed especially for tumor volumes, called generalized Tumor Dose (gTD). It also investigates, as a second objective, margins extensions for potential improvements in local control while maintaining or minimizing toxicity. The suitability of gTD to rank LC was assessed by means of retrospective studies in a head and neck (HN) squamous cell carcinoma (SCC) and non-small cell lung cancer (NSCLC) cohorts. The formulation was optimized based on two datasets (one of each type) and then, model validation was assessed on independent cohorts. The second objective of this dissertation was investigated by ranking the probability of LC of the primary disease adding different margin sizes. In order to do so, an already published EUD formula was used retrospectively in a HN and a NSCLC datasets. Finally, recommendations for the viability to implement this new formulation into a routine treatment

  14. A Rule-Based Industrial Boiler Selection System

    NASA Astrophysics Data System (ADS)

    Tan, C. F.; Khalil, S. N.; Karjanto, J.; Tee, B. T.; Wahidin, L. S.; Chen, W.; Rauterberg, G. W. M.; Sivarao, S.; Lim, T. L.

    2015-09-01

    Boiler is a device used for generating the steam for power generation, process use or heating, and hot water for heating purposes. Steam boiler consists of the containing vessel and convection heating surfaces only, whereas a steam generator covers the whole unit, encompassing water wall tubes, super heaters, air heaters and economizers. The selection of the boiler is very important to the industry for conducting the operation system successfully. The selection criteria are based on rule based expert system and multi-criteria weighted average method. The developed system consists of Knowledge Acquisition Module, Boiler Selection Module, User Interface Module and Help Module. The system capable of selecting the suitable boiler based on criteria weighted. The main benefits from using the system is to reduce the complexity in the decision making for selecting the most appropriate boiler to palm oil process plant.

  15. Optimizing Decision Support for Tailored Health Behavior Change Applications.

    PubMed

    Kukafka, Rita; Jeong, In cheol; Finkelstein, Joseph

    2015-01-01

    The Tailored Lifestyle Change Decision Aid (TLC DA) system was designed to provide support for a person to make an informed choice about which behavior change to work on when multiple unhealthy behaviors are present. TLC DA can be delivered via web, smartphones and tablets. The system collects a significant amount of information that is used to generate tailored messages to consumers to persuade them in certain healthy lifestyles. One limitation is the necessity to collect vast amounts of information from users who manually enter. By identifying an optimal set of self-reported parameters we will be able to minimize the data entry burden of the app users. The study was to identify primary determinants of health behavior choices made by patients after using the system. Using discriminant analysis an optimal set of predictors was identified. The resulting set included smoking status, smoking cessation success estimate, self-efficacy, body mass index and diet status. Predicting smoking cessation choice was the most accurate, followed by weight management. Physical activity and diet choices were better identified in a combined cluster. PMID:26262020

  16. Development and commissioning of decision support tools for sewerage management.

    PubMed

    Manic, G; Printemps, C; Zug, M; Lemoine, C

    2006-01-01

    Managing sewerage systems is a highly complex task due to the dynamic nature of the facilities. Their performance strongly depends on the know-how applied by the operators. In order to define optimal operational settings, two decision support tools based on mathematical models have been developed. Moreover, easy-to-use interfaces have been created as well, aiding operators who presumably do not have the necessary skills to use modelling software. The two developed programs simulate the behaviour of both wastewater treatment plants (WWTP) and sewer network systems, respectively. They have essentially the same structure, including raw data management and statistical analysis, a simulation layer using the application programming interface of the applied software and a layer responsible for the representation of the obtained results. Four user modes are provided in the two software including the simulation of historical data using the applied and novel operational settings, as well as modes concerning prediction of possible operation periods and updates. Concerning the WWTP software, it was successfully installed in Nantes (France) in June 2004. Moreover, the one managing sewer networks has been deployed in Saint-Malo (France) in January 2005. This paper presents the structure of the developed software and the first results obtained during the commissioning phase.

  17. Automation, decision support, and expert systems in nephrology.

    PubMed

    Soman, Sandeep; Zasuwa, Gerard; Yee, Jerry

    2008-01-01

    Increasing data suggest that errors in medicine occur frequently and result in substantial harm to the patient. The Institute of Medicine report described the magnitude of the problem, and public interest in this issue, which was already large, has grown. The traditional approach in medicine has been to identify the persons making the errors and recommend corrective strategies. However, it has become increasingly clear that it is more productive to focus on the systems and processes through which care is provided. If these systems are set up in ways that would both make errors less likely and identify those that do occur and, at the same time, improve efficiency, then safety and productivity would be substantially improved. Clinical decision support systems (CDSSs) are active knowledge systems that use 2 or more items of patient data to generate case specific recommendations. CDSSs are typically designed to integrate a medical knowledge base, patient data, and an inference engine to generate case specific advice. This article describes how automation, templating, and CDSS improve efficiency, patient care, and safety by reducing the frequency and consequences of medical errors in nephrology. We discuss practical applications of these in 3 settings: a computerized anemia-management program (CAMP, Henry Ford Health System, Detroit, MI), vascular access surveillance systems, and monthly capitation notes in the hemodialysis unit.

  18. Artificial neural networks for decision support in clinical medicine.

    PubMed

    Forsström, J J; Dalton, K J

    1995-10-01

    Connectionist models such as neural networks are alternatives to linear, parametric statistical methods. Neural networks are computer-based pattern recognition methods with loose similarities with the nervous system. Individual variables of the network, usually called 'neurones', can receive inhibitory and excitatory inputs from other neurones. The networks can define relationships among input data that are not apparent when using other approaches, and they can use these relationships to improve accuracy. Thus, neural nets have substantial power to recognize patterns even in complex datasets. Neural network methodology has outperformed classical statistical methods in cases where the input variables are interrelated. Because clinical measurements usually derive from multiple interrelated systems it is evident that neural networks might be more accurate than classical methods in multivariate analysis of clinical data. This paper reviews the use of neural networks in medical decision support. A short introduction to the basics of neural networks is given, and some practical issues in applying the networks are highlighted. The current use of neural networks in image analysis, signal processing and laboratory medicine is reviewed. It is concluded that neural networks have an important role in image analysis and in signal processing. However, further studies are needed to determine the value of neural networks in the analysis of laboratory data.

  19. Effectively marketing prepaid medical care with decision support systems.

    PubMed

    Forgionne, G A

    1991-01-01

    The paper reports a decision support system (DSS) that enables health plan administrators to quickly and easily: (1) manage relevant medical care market (consumer preference and competitors' program) information and (2) convert the information into appropriate medical care delivery and/or payment policies. As the paper demonstrates, the DSS enables providers to design cost efficient and market effective medical care programs. The DSS provides knowledge about subscriber preferences, customer desires, and the program offerings of the competition. It then helps administrators structure a medical care plan in a way that best meets consumer needs in view of the competition. This market effective plan has the potential to generate substantial amounts of additional revenue for the program. Since the system's data base consists mainly of the provider's records, routine transactions, and other readily available documents, the DSS can be implemented at a nominal incremental cost. The paper also evaluates the impact of the information system on the general financial performance of existing dental and mental health plans. In addition, the paper examines how the system can help contain the cost of providing medical care while providing better services to more potential beneficiaries than current approaches.

  20. Computerized decision support systems: improving patient safety in nephrology

    PubMed Central

    Chang, Jamison; Ronco, Claudio; Rosner, Mitchell H.

    2016-01-01

    Incorrect prescription and administration of medications account for a substantial proportion of medical errors in the USA, causing adverse drug events (ADEs) that result in considerable patient morbidity and enormous costs to the health-care system. Patients with chronic kidney disease or acute kidney injury often have impaired drug clearance as well as polypharmacy, and are therefore at increased risk of experiencing ADEs. Studies have demonstrated that recognition of these conditions is not uniform among treating physicians, and prescribed drug doses are often incorrect. Early interventions that ensure appropriate drug dosing in this group of patients have shown encouraging results. Both computerized physician order entry and clinical decision support systems have been shown to reduce the rate of ADEs. Nevertheless, these systems have been implemented at surprisingly few institutions. Economic stimulus and health-care reform legislation present a rare opportunity to refine these systems and understand how they could be implemented more widely. Failure to explore this technology could mean that the opportunity to reduce the morbidity associated with ADEs is missed. PMID:21502973

  1. Why decision support systems are important for medical education.

    PubMed

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified.

  2. A Semantic Sensor Web for Environmental Decision Support Applications

    PubMed Central

    Gray, Alasdair J. G.; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A. A.; Paton, Norman W.; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

    2011-01-01

    Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England. PMID:22164110

  3. Agricultural Model for the Nile Basin Decision Support System

    NASA Astrophysics Data System (ADS)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

    To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

  4. Why decision support systems are important for medical education.

    PubMed

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified. PMID:27222734

  5. A semantic sensor web for environmental decision support applications.

    PubMed

    Gray, Alasdair J G; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A A; Paton, Norman W; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

    2011-01-01

    Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.

  6. Simulation of large-scale rule-based models

    SciTech Connect

    Hlavacek, William S; Monnie, Michael I; Colvin, Joshua; Faseder, James

    2008-01-01

    Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models. DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein-protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of STOCHSIM. DYNSTOC differs from STOCHSIM by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions. DYNSTOC is free for non-commercial use. The C source code, supporting documentation and example input files are available at .

  7. Computer aided decision support system for cervical cancer classification

    NASA Astrophysics Data System (ADS)

    Rahmadwati, Rahmadwati; Naghdy, Golshah; Ros, Montserrat; Todd, Catherine

    2012-10-01

    Conventional analysis of a cervical histology image, such a pap smear or a biopsy sample, is performed by an expert pathologist manually. This involves inspecting the sample for cellular level abnormalities and determining the spread of the abnormalities. Cancer is graded based on the spread of the abnormal cells. This is a tedious, subjective and time-consuming process with considerable variations in diagnosis between the experts. This paper presents a computer aided decision support system (CADSS) tool to help the pathologists in their examination of the cervical cancer biopsies. The main aim of the proposed CADSS system is to identify abnormalities and quantify cancer grading in a systematic and repeatable manner. The paper proposes three different methods which presents and compares the results using 475 images of cervical biopsies which include normal, three stages of pre cancer, and malignant cases. This paper will explore various components of an effective CADSS; image acquisition, pre-processing, segmentation, feature extraction, classification, grading and disease identification. Cervical histological images are captured using a digital microscope. The images are captured in sufficient resolution to retain enough information for effective classification. Histology images of cervical biopsies consist of three major sections; background, stroma and squamous epithelium. Most diagnostic information are contained within the epithelium region. This paper will present two levels of segmentations; global (macro) and local (micro). At the global level the squamous epithelium is separated from the background and stroma. At the local or cellular level, the nuclei and cytoplasm are segmented for further analysis. Image features that influence the pathologists' decision during the analysis and classification of a cervical biopsy are the nuclei's shape and spread; the ratio of the areas of nuclei and cytoplasm as well as the texture and spread of the abnormalities

  8. Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

    PubMed Central

    Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

    2014-01-01

    Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

  9. Virtual Beach: Decision Support Tools for Beach Pathogen Prediction

    EPA Science Inventory

    The Virtual Beach Managers Tool (VB) is decision-making software developed to help local beach managers make decisions as to when beaches should be closed due to predicted high levels of water borne pathogens. The tool is being developed under the umbrella of EPA's Advanced Monit...

  10. Decision Support Systems: Applications in Statistics and Hypothesis Testing.

    ERIC Educational Resources Information Center

    Olsen, Christopher R.; Bozeman, William C.

    1988-01-01

    Discussion of the selection of appropriate statistical procedures by educators highlights a study conducted to investigate the effectiveness of decision aids in facilitating the use of appropriate statistics. Experimental groups and a control group using a printed flow chart, a computer-based decision aid, and a standard text are described. (11…

  11. An Oceanographic Decision Support System for Scientific Field Experiments

    NASA Astrophysics Data System (ADS)

    Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.

    2011-12-01

    Thom Maughan, Jnaneshwar Das, Mike McCann, Danelle Cline, Mike Godin, Fred Bahr, Kevin Gomes, Tom O'Reilly, Frederic Py, Monique Messie, John Ryan, Francisco Chavez, Jim Bellingham, Maria Fox, Kanna Rajan Monterey Bay Aquarium Research Institute Moss Lading, California, United States Many of the coastal ocean processes we wish to observe in order to characterize marine ecosystems have large spatial extant (tens of square km) and are dynamic moving kilometers in a day with biological processes spanning anywhere from minutes to days. Some like harmful algal blooms generate toxins which can significantly impact human health and coastal economies. In order to obtain a viable understanding of the biogeochemical processes which define their dynamics and ecology, it is necessary to persistently observe, track and sample within and near the dynamic fields using augmented methods of observation such as autonomous platforms like AUVs, gliders and surface craft. Field experiments to plan, execute and manage such multitude of assets are challenging. To alleviate this problem the autonomous systems group with its collaborators at MBARI and USC designed, built and fielded a prototype Oceanographic Decision Support System (ODSS) that provides situational awareness and a single portal to visualize and plan deployments for the large scale October 2010 CANON field program as well as a series of 2 week field programs in 2011. The field programs were conducted in Monterey Bay, a known 'red tide' incubator, and varied from as many as twenty autonomous platforms, four ships and 2 manned airplanes to coordinated AUV operations, drifters and a single ship. The ODSS web-based portal was used to assimilate information from a collection of sources at sea, including AUVs, moorings, radar data as well as remote sensing products generated by partner organizations to provide a synthesis of views useful to predict the movement of a chlorophyll patch in the confines of the northern Monterey Bay

  12. Interactive decision support system to predict print quality.

    PubMed

    Leman, Sugani; Lehto, Mark R

    2003-01-15

    Customers using printers occasionally experience problems such as fuzzy images, bands, or streaks. The customer may call or otherwise contact the manufacturer, who attempts to diagnose the problem based on the customer's description of the problem. This study evaluated Bayesian inference as a tool for identifying or diagnosing 16 different types of print defects from such descriptions. The Bayesian model was trained using 1701 narrative descriptions of print defects obtained from 60 subjects with varying technical backgrounds. The Bayesian model was then implemented as an interactive decision support system, which was used by eight 'agents' to diagnose print defects reported by 16 'customers' in a simulated call centre. The 'agents' and 'customers' in the simulated call centre were all students at Purdue University. Each customer made eight telephone calls, resulting in a total of 128 telephone calls in which the customer reported defects to the agents. The results showed that the Bayesian model closely fitted the data in the training set of narratives. Overall, the model correctly predicted the actual defect category with its top prediction 70% of the time. The actual defect was in the top five predictions 94% of the time. The model in the simulated call centre performed nearly as well for the test subjects. The top prediction was correct 50% of the time, and the defect was one of the top five predictions 80% of the time. Agent accuracy in diagnosing the problem improved when using the tool. These results demonstrated that the Bayesian system learned enough from the existing narratives to accurately classify print defect categories.

  13. A decision support system for managing forest fire casualties.

    PubMed

    Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos

    2007-09-01

    Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns. PMID:16928418

  14. Decision support system for monitoring environmental-human interactions.

    PubMed

    Delavari-Edalat, Farideh; Abdi, M Reza

    2009-06-01

    The specific aim of this study is to investigate popular attitudes toward trees. The paper is involved the understanding of biophilia tendencies with respect to people's views in an urban area. Biophilia is considered as the idea insisting on the dependency of human identity on his relationship with nature. The biophilia fundamental tendencies were explored to establish a biological framework for valuing and affiliating the natural world. Accordingly, the nine tendencies i.e. utilitarian, naturalistic, ecologistic-scientific, aesthetic, symbolic, humanistic, moralistic, dominionistic, and negativistic were investigate to find out how people relate to the nature especially trees. The investigation was based on a quantitative interview which was applied to the public population in the Liverpool urban parks. Data collected from the designed questionnaire was followed by analysis of the data to identify people's attitudes towards trees. The results indicated how important the physical appeal and beauty of trees was for the people and also showed the people's emotional attachments to trees. Furthermore, a decision support model was proposed to evaluate human instincts and preferences in relation to their surrounding areas using the Analytical Hierarchical Process (AHP). The proposed model composed the environmental factors and the biophilia tendencies as the criteria of evaluating environmental-human interactions. A case study was then conducted in Liverpool parks to examine theses interactions. The data gathered was used as the input to the AHP model for the attribute analysis. The AHP model would enable environment managers to compose the relevant information via a link between human feelings about urban trees, and environmental factors for monitoring purposes and performance analysis.

  15. A decision support system for managing forest fire casualties.

    PubMed

    Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos

    2007-09-01

    Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns.

  16. Air Traffic Control Decision Support Tools for Noise Mitigation

    NASA Technical Reports Server (NTRS)

    Tobias, Leonard

    2001-01-01

    NASA has initiated a new five year program this year, the Quiet Aircraft Technology (QAT) Program, a program which will investigate airframe and engine system noise reduction. QAT will also address community noise impact. As part of this community noise impact component, NASA will investigate air traffic management (ATM) challenges in reducing noise. In particular, controller advisory automation aids will be developed to aid the air traffic controller in addressing noise concerns as he/she manages traffic in busy terminal areas. NASA has developed controller automation tools to address capacity concerns and the QAT strategy for ATM Low Noise Operations is to build upon this tool set to create added advisories for noise mitigation. The tools developed for capacity will be briefly reviewed, followed by the QAT plans to address ATM noise concerns. A major NASA goal in global civil aviation is to triple the aviation system throughput in all-weather conditions while maintaining safety. A centerpiece of this activity is the Center/TRACON Automation System (CTAS), an evolving suite of air traffic controller decision support tools (DSTs) to enhance capacity of arrivals and departures in both the enroute center and the TRACON. Two of these DSTs, the Traffic Management Advisor (TMA) and the passive Final approach Spacing Tool (pFAST), are in daily use at the Fort Worth Center and the Dallas/Fort Worth (DFW) TRACON, respectively, where capacity gains of 5-13% have been reported in recent NASA evaluations. Under the Federal Aviation Administration's (FAA) Free Flight Phase One Program, TMA and pFAST are each being implemented at six to eight additional sites. In addition, other DSTs are being developed by NASA under the umbrella of CTAS. This means that new software will be built upon CTAS, and the paradigm of real-time simulation evaluation followed by field site development and evaluation will be the pathway for the new tools. Additional information is included in the

  17. MAROS: a decision support system for optimizing monitoring plans.

    PubMed

    Aziz, Julia J; Ling, Meng; Rifai, Hanadi S; Newell, Charles J; Gonzales, James R

    2003-01-01

    The Monitoring and Remediation Optimization System (MAROS), a decision-support software, was developed to assist in formulating cost-effective ground water long-term monitoring plans. MAROS optimizes an existing ground water monitoring program using both temporal and spatial data analyses to determine the general monitoring system category and the locations and frequency of sampling for future compliance monitoring at the site. The objective of the MAROS optimization is to minimize monitoring locations in the sampling network and reduce sampling frequency without significant loss of information, ensuring adequate future characterization of the contaminant plume. The interpretive trend analysis approach recommends the general monitoring system category for a site based on plume stability and site-specific hydrogeologic information. Plume stability is characterized using primary lines of evidence (i.e., Mann-Kendall analysis and linear regression analysis) based on concentration trends, and secondary lines of evidence based on modeling results and empirical data. The sampling optimization approach, consisting of a two-dimensional spatial sampling reduction method (Delaunay method) and a temporal sampling analysis method (Modified CES method), provides detailed sampling location and frequency results. The Delaunay method is designed to identify and eliminate redundant sampling locations without causing significant information loss in characterizing the plume. The Modified CES method determines the optimal sampling frequency for a sampling location based on the direction, magnitude, and uncertainty in its concentration trend. MAROS addresses a variety of ground water contaminants (fuels, solvents, and metals), allows import of various data formats, and is designed for continual modification of long-term monitoring plans as the plume or site conditions change over time.

  18. Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

    NASA Technical Reports Server (NTRS)

    Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan

    2000-01-01

    The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an

  19. Clinical Decision Support and Closed-Loop Control for Cardiopulmonary Management and Intensive Care Unit Sedation Using Expert Systems.

    PubMed

    Gholami, Behnood; Bailey, James M; Haddad, Wassim M; Tannenbaum, Allen R

    2012-03-01

    Patients in the intensive care unit (ICU) who require mechanical ventilation due to acute respiratory failure also frequently require the administration of sedative agents. The need for sedation arises both from patient anxiety due to the loss of personal control and the unfamiliar and intrusive environment of the ICU, and also due to pain or other variants of noxious stimuli. While physicians select the agent(s) used for sedation and cardiovascular function, the actual administration of these agents is the responsibility of the nursing staff. If clinical decision support systems and closed-loop control systems could be developed for critical care monitoring and lifesaving interventions as well as the administration of sedation and cardiopulmonary management, the ICU nurse could be released from the intense monitoring of sedation, allowing her/him to focus on other critical tasks. One particularly attractive strategy is to utilize the knowledge and experience of skilled clinicians, capturing explicitly the rules expert clinicians use to decide on how to titrate drug doses depending on the level of sedation. In this paper, we extend the deterministic rule-based expert system for cardiopulmonary management and ICU sedation framework presented in [1] to a stochastic setting by using probability theory to quantify uncertainty and hence deal with more realistic clinical situations.

  20. ALC: automated reduction of rule-based models

    PubMed Central

    Koschorreck, Markus; Gilles, Ernst Dieter

    2008-01-01

    Background Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously. Results ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website. Conclusion ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files. PMID:18973705

  1. User Oriented Techniques to Support Interaction and Decision Making with Large Educational Databases

    ERIC Educational Resources Information Center

    Hartley, Roger; Almuhaidib, Saud M. Y.

    2007-01-01

    Information Technology is developing rapidly and providing policy/decision makers with large amounts of information that require processing and analysis. Decision support systems (DSS) aim to provide tools that not only help such analyses, but enable the decision maker to experiment and simulate the effects of different policies and selection…

  2. Estimating the Horizon of articles to decide when to stop searching in systematic reviews: an example using a systematic review of RCTs evaluating osteoporosis clinical decision support tools.

    PubMed

    Kastner, Monika; Straus, Sharon; Goldsmith, Charlie H

    2007-10-11

    Researchers conducting systematic reviews need to search multiple bibliographic databases such as MEDLINE and EMBASE. However, researchers have no rational search stopping rule when looking for potentially-relevant articles. We empirically tested a stopping rule based on the concept of capture-mark-recapture (CMR), which was first pioneered in ecology. The principles of CMR can be adapted to systematic reviews and meta-analyses to estimate the Horizon of articles in the literature with its confidence interval. We retrospectively tested this Horizon Estimation using a systematic review of randomized controlled trials (RCTs) that evaluated clinical decision support tools for osteoporosis disease management. The Horizon Estimation was calculated based on 4 bibliographic databases that were included as the main data sources for the review in the following order: MEDLINE, EMBASE, CINAHL, and EBM Reviews. The systematic review captured 68% of known articles from the 4 data sources, which represented 592 articles that were estimated as missing from the Horizon.

  3. Investing in deliberation: a definition and classification of decision support interventions for people facing difficult health decisions.

    PubMed

    Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M

    2010-01-01

    This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.

  4. SADA: Ecological Risk Based Decision Support System for Selective Remediation

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

  5. Hydrologic Drought Decision Support System (HyDroDSS)

    USGS Publications Warehouse

    Granato, Gregory E.

    2014-01-01

    The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions

  6. 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.

  7. Structured decision making as a framework for linking quantitative decision support to community values

    EPA Science Inventory

    Community-level decisions can have large impacts on production and delivery of ecosystem services, which ultimately affects community well-being. But engaging stakeholders in a process to explore these impacts is a significant challenge. The principles of Structured Decision Ma...

  8. A Decision Support System For Assisting With Stocking Rate Decisions During And Following Drought

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ranchers and range managers in the West are at the mercy of climatic conditions that determine the amount of annual forge available on rangeland. Typically, stocking or de-stocking decisions need to be made before the final forage production level is known. Erroneous stocking rate decisions can have...

  9. Methodology for the use of DSSAT Models for Precision Agriculture Decision Support

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A prototype decision support system (DSS) called Apollo was developed to assist researchers in using the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth models to analyze precision farming datasets. Because the DSSAT models are written to simulate crop growth and development...

  10. Introduction to Decision Support Systems for Risk Based Management of Contaminated Sites

    EPA Science Inventory

    A book on Decision Support Systems for Risk-based Management of contaminated sites is appealing for two reasons. First, it addresses the problem of contaminated sites, which has worldwide importance. Second, it presents Decision Support Systems (DSSs), which are powerful comput...

  11. Validation of a decision support system for improving irrigation system performance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To address water shortage and improve water delivery operations, decision support systems have been developed and utilized throughout the United States and the world. One critical aspect that is often neglected during the development and implementation of decision support systems is validation, whi...

  12. Decision Support Systems Project. Design Review Conference, October 14-15, 1984. Summary Report of Findings.

    ERIC Educational Resources Information Center

    Tetlow, William L.

    Findings of a conference that reviewed and evaluated design decisions concerning the Decision Support System (DSS) Demonstrator are summarized. The DSS Demonstrator was designed by the National Center for Higher Education Management Systems as an example of the way in which microcomputer technology can support and make more effective planning and…

  13. Academic Support Services and Career Decision-Making Self-Efficacy in Student Athletes

    ERIC Educational Resources Information Center

    Burns, Gary N.; Jasinski, Dale; Dunn, Steve; Fletcher, Duncan

    2013-01-01

    This study examined the relationship between evaluations of academic support services and student athletes' career decision-making self-efficacy. One hundred and fifty-eight NCAA athletes (68% male) from 11 Division I teams completed measures of satisfaction with their academic support services, career decision-making self-efficacy, general…

  14. Supporting patient autonomy: decision making in home care.

    PubMed

    Davitt, J K; Kaye, L W

    1996-01-01

    This study examines the policies and procedures that home health care agencies have developed to handle the incapacitated patient and life-sustaining treatment decisions. Data collected from a survey of 154 home health care agency directors and interviews with 92 local agency staff (including nurses and social workers) and 67 patients confirmed that directors, staff, and patients agree that patients are informed about their legal rights. When asked about specific rights, fewer patients were aware of their right to execute an advance directive, and even fewer patients had actually executed one. Only 67 percent of agencies reported having existing policies on advance directives and life-sustaining treatment decisions, whereas 41.5 percent had policies on how to handle the patient with questionable decision-making capacity. Consistent policies are needed for social workers, nurses, and other staff to handle such difficult ethical dilemmas. A review of specific agency policies is presented with recommendations for future policy changes and development.

  15. Nonword repetition in lexical decision: support for two opposing processes.

    PubMed

    Wagenmakers, Eric-Jan; Zeelenberg, René; Steyvers, Mark; Shiffrin, Richard; Raaijmakers, Jeroen

    2004-10-01

    We tested and confirmed the hypothesis that the prior presentation of nonwords in lexical decision is the net result of two opposing processes: (1) a relatively fast inhibitory process based on global familiarity; and (2) a relatively slow facilitatory process based on the retrieval of specific episodic information. In three studies, we manipulated speed-stress to influence the balance between the two processes. Experiment 1 showed item-specific improvement for repeated nonwords in a standard "respond-when-ready" lexical decision task. Experiment 2 used a 400-ms deadline procedure and showed performance for nonwords to be unaffected by up to four prior presentations. In Experiment 3 we used a signal-to-respond procedure with variable time intervals and found negative repetition priming for repeated nonwords. These results can be accounted for by dual-process models of lexical decision.

  16. A rule-based software test data generator

    NASA Technical Reports Server (NTRS)

    Deason, William H.; Brown, David B.; Chang, Kai-Hsiung; Cross, James H., II

    1991-01-01

    Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

  17. Mountaineer`s gas facilities decision support system

    SciTech Connect

    1997-02-01

    Mountaineer Gas Co. of Charleston, W.Va., is justifiably proud of its capacity to combine electronic maps with a full database of information about its facilities and customers, and use that mix to make the decisions required in operating a gas company with better information and more quickly. Determining when a pipeline needs replacement or repair used to take several days at Mountaineer. With the new system in place, the decision can be made in a matter of minutes. The paper describes the system and its development, then discusses adding customer information as the next step.

  18. A Pain Management Decision Support System for Nurses

    PubMed Central

    Heriot, Cathy; Graves, Judith; Bouhaddou, Omar; Armstrong, Margaret; Wigertz, Gudrun; Ben Said, Mohamed

    1988-01-01

    This paper describes the development and uses of the Nursing Pain Management Consultation System, a prototype demonstration project for Integrated Academic Information Management System (IAIMS) at the University of Utah. A knowledge base representing the best current thinking regarding management of acute pain secondary to total hip arthroplasty (THA) is the knowledge core of the expert system. The decisions modeled range from assessment of the severity of pain to decisions related to both pharmacologic and non-pharmacologic approaches to the alleviation of pain. The system also advises the nurses on measures to assess and prevent complications of the treatments.

  19. Coordinated machine learning and decision support for situation awareness.

    PubMed

    Brannon, N G; Seiffertt, J E; Draelos, T J; Wunsch, D C

    2009-04-01

    Domains such as force protection require an effective decision maker to maintain a high level of situation awareness. A system that combines humans with neural networks is a desirable approach. Furthermore, it is advantageous for the calculation engine to operate in three learning modes: supervised for initial training and known updating, reinforcement for online operational improvement, and unsupervised in the absence of all external signaling. An Adaptive Resonance Theory based architecture capable of seamlessly switching among the three types of learning is discussed that can be used to help optimize the decision making of a human operator in such a scenario. This is followed by a situation assessment module.

  20. Decision Support Services provided by the NWS Alaska Regional Operations Center in 2015

    NASA Astrophysics Data System (ADS)

    van Breukelen, C. M.; Osiensky, J. M.

    2015-12-01

    The NWS Alaska Region's Regional Operations Center (AR ROC) provides a variety of decision support services to partners and customers across the state. The AR ROC is virtual most times but can flex to stand up support for partners as needed. Support can vary from briefings over the phone or in person to dedicated virtual support to providing on-site meteorologist at an Emergency Operations Center or Incident Command Post to provide tailored support services. During 2015 there have been a number of situations where the AR ROC provided unique support services. This presentation will outline a few examples of how these unique support services benefitted partner agency decisions.

  1. A high-level language for rule-based modelling.

    PubMed

    Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D

    2015-01-01

    Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages. PMID:26043208

  2. A high-level language for rule-based modelling.

    PubMed

    Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D

    2015-01-01

    Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

  3. Haunted by a doppelgänger: irrelevant facial similarity affects rule-based judgments.

    PubMed

    von Helversen, Bettina; Herzog, Stefan M; Rieskamp, Jörg

    2014-01-01

    Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment. PMID:23895921

  4. ENVIRONMENTAL FEATURE FINDER: A REMOTE SENSING DECISION SUPPORT TOOL

    EPA Science Inventory

    Land cover maps are essential to sound environmental stewardship and EPA’s mission to protect human health and the environment, but existing maps are not always sufficiently current, detailed, or appropriate for a given application. Consequently, we are developing a decision sup...

  5. Improving Information Products for System 2 Decision Support

    ERIC Educational Resources Information Center

    Gibson, Neal

    2010-01-01

    The creation, maintenance, and management of Information Product (IP) systems that are used by organizations for complex decisions represent a unique set of challenges. These challenges are compounded when the purpose of such a systems is also for knowledge creation and dissemination. Information quality research to date has focused mainly upon…

  6. Managerial Analysis and Decision Support: A Guidebook and Case Studies

    ERIC Educational Resources Information Center

    National Association of College and University Business Officers (NJ3), 2004

    2004-01-01

    Developed and edited by the National Association of College and University Business Officers' (NACUBO's) Accounting Principles Council, this guidebook, written by highly experienced, seasoned college and university leaders, is designed to help readers make sense of today's world and provide the right tools to make the right decisions. The book,…

  7. Hydrologic Drought Decision Support System (HyDroDSS)

    USGS Publications Warehouse

    Granato, Gregory E.

    2014-01-01

    The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions

  8. Implementation of workflow engine technology to deliver basic clinical decision support functionality

    PubMed Central

    2011-01-01

    Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of

  9. Decision support models for solid waste management: Review and game-theoretic approaches

    SciTech Connect

    Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

    2013-05-15

    Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.

  10. Translating Knowledge into Action: Supporting Adaptation in Australia's Coastal Zone through Information Provision and Decision Support

    NASA Astrophysics Data System (ADS)

    Palutikof, J. P.; Rissik, D.; Tonmoy, F. N.; Boulter, S.

    2015-12-01

    Adaptation to risks from climate change and sea-level rise is particularly important in Australia, where 70% of the population live in major coastal cities and 85% within 50km of the coast. Adaptation activity focuses at local government level and, in the absence of strong leadership from central government, the extent to which local councils have taken action to adapt is highly variable across the nation. Also, although a number of councils have proceeded as far as identifying their exposure to risk and considering adaptation options, this fails to translate into action. A principal reason for this is concern over the response from coastal residents to actions which may affect property values, and fear of litigation. A project is underway to support councils to understand their risks, evaluate adaptation options and proceed to action. This support will consist of a three-pronged framework: provision of information, a tool to support decision-making, and a community forum. Delivery involves research to understand the barriers to adaptation and how these may be overcome, optimal methods for delivery of information, and the information needs of organizations, action-takers and communities. The presentation will focus on the results of consultation undertaken to understand users' information needs around content and delivery, and how understanding of these needs has translated into design of the framework. A strongly preference was expressed to learn from peers, and a challenge for the framework is to understand how to inject adaptation knowledge which is up-to-date and accurate into peer-to-peer conversations. The community forum is one mechanism to achieve this. The basic structure and delivery mechanisms of the framework are shown in the attached.

  11. Developing Climate Resilience Toolkit Decision Support Training Sectio

    NASA Astrophysics Data System (ADS)

    Livezey, M. M.; Herring, D.; Keck, J.; Meyers, J. C.

    2014-12-01

    The Climate Resilience Toolkit (CRT) is a Federal government effort to address the U.S. President's Climate Action Plan and Executive Order for Climate Preparedness. The toolkit will provide access to tools and products useful for climate-sensitive decision making. To optimize the user experience, the toolkit will also provide access to training materials. The National Oceanic and Atmospheric Administration (NOAA) has been building a climate training capability for 15 years. The target audience for the training has historically been mainly NOAA staff with some modified training programs for external users and stakeholders. NOAA is now using this climate training capacity for the CRT. To organize the CRT training section, we collaborated with the Association of Climate Change Officers to determine the best strategy and identified four additional complimentary skills needed for successful decision making: climate literacy, environmental literacy, risk assessment and management, and strategic execution and monitoring. Developing the climate literacy skills requires knowledge of climate variability and change, as well as an introduction to the suite of available products and services. For the development of an environmental literacy category, specific topics needed include knowledge of climate impacts on specific environmental systems. Climate risk assessment and management introduces a process for decision making and provides knowledge on communication of climate information and integration of climate information in planning processes. The strategic execution and monitoring category provides information on use of NOAA climate products, services, and partnership opportunities for decision making. In order to use the existing training modules, it was necessary to assess their level of complexity, catalog them, and develop guidance for users on a curriculum to take advantage of the training resources to enhance their learning experience. With the development of this CRT

  12. Economic Evaluation of Environmental Health Interventions to Support Decision Making

    PubMed Central

    Hutton, Guy

    2008-01-01

    Environmental burden of disease represents one quarter of overall disease burden, hence necessitating greater attention from decision makers both inside and outside the health sector. Economic evaluation techniques such as cost-effectiveness analysis and cost-benefit analysis provide key information to health decision makers on the efficiency of environmental health interventions, assisting them in choosing interventions which give the greatest social return on limited public budgets and private resources. The aim of this article is to review economic evaluation studies in three environmental health areas—water, sanitation, hygiene (WSH), vector control, and air pollution—and to critically examine the policy relevance and scientific quality of the studies for selecting and funding public programmers. A keyword search of Medline from 1990–2008 revealed 32 studies, and gathering of articles from other sources revealed a further 18 studies, giving a total of 50 economic evaluation studies (13 WSH interventions, 16 vector control and 21 air pollution). Overall, the economic evidence base on environmental health interventions remains relatively weak—too few studies per intervention, of variable scientific quality and from diverse locations which limits generalisability of findings. Importantly, there still exists a disconnect between economic research, decision making and programmer implementation. This can be explained by the lack of translation of research findings into accessible documentation for policy makers and limited relevance of research findings, and the often low importance of economic evidence in budgeting decisions. These findings underline the importance of involving policy makers in the defining of research agendas and commissioning of research, and improving the awareness of researchers of the policy environment into which their research feeds. PMID:21572840

  13. Consensus oriented fuzzified decision support for oil spill contingency management.

    PubMed

    Liu, Xin; Wirtz, Kai W

    2006-06-30

    Studies on multi-group multi-criteria decision-making problems for oil spill contingency management are in their infancy. This paper presents a second-order fuzzy comprehensive evaluation (FCE) model to resolve decision-making problems in the area of contingency management after environmental disasters such as oil spills. To assess the performance of different oil combat strategies, second-order FCE allows for the utilization of lexical information, the consideration of ecological and socio-economic criteria and the involvement of a variety of stakeholders. On the other hand, the new approach can be validated by using internal and external checks, which refer to sensitivity tests regarding its internal setups and comparisons with other methods, respectively. Through a case study, the Pallas oil spill in the German Bight in 1998, it is demonstrated that this approach can help decision makers who search for an optimal strategy in multi-thread contingency problems and has a wider application potential in the field of integrated coastal zone management.

  14. Ecosystem Decision Support: A Living Database of Existing Tools, Approaches and Techniques for Supporting Decisions Related to Ecosystem Services

    EPA Science Inventory

    Planners and decision makers are challenged to consider not only direct market costs, but also ecological externalities. There is an increasing emphasis on ecosystem services in the context of human well-being, and therefore the valuation and accounting of ecosystem services is b...

  15. SANDS: A Service-Oriented Architecture for Clinical Decision Support in a National Health Information Network

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. PMID:18434256

  16. CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

    SciTech Connect

    Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.; Strasburg, Jana D.

    2011-11-15

    We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

  17. Coordinated machine learning and decision support for situation awareness.

    SciTech Connect

    Draelos, Timothy John; Zhang, Peng-Chu.; Wunsch, Donald C.; Seiffertt, John; Conrad, Gregory N.; Brannon, Nathan Gregory

    2007-09-01

    For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.

  18. Decision Support Systems and Line Performance: Case of Gold Coast University Hospital.

    PubMed

    Connor, Martin; Ghapanchi, Amir Hossein; Blumenstein, Michael; Amrollahi, Alireza; Najaftorkaman, Mohammadreza

    2015-01-01

    Computer-based decision support information systems have been promoted for their potential to improve physician performance and patient outcomes and support clinical decision making. The current case study reported design and implementation of a high-level decision support system (DSS) which facilitated the flow of data from operational level to top managers and leadership level of hospitals. The results shows that development of a DSS improve data connectivity, timing, and responsiveness issues via centralised sourcing and storing of principal health-related information in the hospital. The implementation of the system has resulted in significant enhancements in outpatient waiting times management.

  19. The Contribution of a Decision Support System to Complex Educational Decisions

    ERIC Educational Resources Information Center

    Klein, Joseph

    2005-01-01

    This study examined the effect of complexity of problems on the degree of disparity between intuitive (PDM) and computer-assisted (DSS) decision-making. 840 teachers chose intuitive solutions for educational dilemmas, and recorded the relative importance of the guiding criteria. Utilizing this information, DSS calculated preferred solutions. Of…

  20. A Proposed Clinical Decision Support Architecture Capable of Supporting Whole Genome Sequence Information

    PubMed Central

    Welch, Brandon M.; Rodriguez Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

    2014-01-01

    Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine. PMID:25411644

  1. Visual Cluster Analysis in Support of Clinical Decision Intelligence

    PubMed Central

    Gotz, David; Sun, Jimeng; Cao, Nan; Ebadollahi, Shahram

    2011-01-01

    Electronic health records (EHRs) contain a wealth of information about patients. In addition to providing efficient and accurate records for individual patients, large databases of EHRs contain valuable information about overall patient populations. While statistical insights describing an overall population are beneficial, they are often not specific enough to use as the basis for individualized patient-centric decisions. To address this challenge, we describe an approach based on patient similarity which analyzes an EHR database to extract a cohort of patient records most similar to a specific target patient. Clusters of similar patients are then visualized to allow interactive visual refinement by human experts. Statistics are then extracted from the refined patient clusters and displayed to users. The statistical insights taken from these refined clusters provide personalized guidance for complex decisions. This paper focuses on the cluster refinement stage where an expert user must interactively (a) judge the quality and contents of automatically generated similar patient clusters, and (b) refine the clusters based on his/her expertise. We describe the DICON visualization tool which allows users to interactively view and refine multidimensional similar patient clusters. We also present results from a preliminary evaluation where two medical doctors provided feedback on our approach. PMID:22195102

  2. Assembling Tools and Data for Climate Model Decision Support

    NASA Astrophysics Data System (ADS)

    Batcheller, A. L.; VanWijngaarden, F.

    2011-12-01

    The Global Earth Observation System of Systems (GEOSS) effort has identified nine areas in which society benefits from appropriate environmental information. We have targeted specific issues within these societal benefit areas by determining appropriate data sets needed and transforming these data into information useable by decision makers. Here we describe the service-oriented architecture that allows us to ingest real-time or static data into a database with a spatial data engine, make appropriate manipulations to the data using domain knowledge relevant to the problem, and expose the data as services. We then build custom portals using a library of common widgets to display and overlay the data for users to analyze. By using portals and a service-oriented architecture we can reuse services and widgets to rapidly assemble a view of geographic data, and assist decision-makers in applying and interpreting the latest scientific results. As a case study with our system, we have integrated data from Intergovernmental Panel on Climate Change (IPCC) climate models, crop yields, and environmental thresholds for crops to present a first level analysis of the impact of climate change on key crops grown in Mexico. Knowledge about changes in the regions that are favorable for crop growth is important for many stakeholders, ranging from individual farmers, to governments, to scientists working to create new seed varieties. Our work also highlights research opportunities in climate science by identifying the types and resolution of parameters modeled.

  3. In and out of home care decisions: The influence of confirmation bias in developing decision supportive reasoning.

    PubMed

    Spratt, Trevor; Devaney, John; Hayes, David

    2015-11-01

    The aims of this study were to identify the themes Social Workers regard as important in supporting decisions to remove children from, or return them to, the care of their parents. To further elicit underlying hypotheses that are discernible in interpretation of evidence. A case study, comprising a two-part vignette with a questionnaire, recorded demographic information, child welfare attitudes and risk assessments, using scales derived from standardised instruments, was completed by 202 Social Workers in Northern Ireland. There were two manipulated variables, mother's attitude to removal and child's attitude to reunification 2 years later. In this paper we use data derived from respondents' qualitative comments explaining their reasoning for in and out of home care decisions. Some 60.9% of respondent's chose the parental care option at part one, with 94% choosing to have the child remain in foster care at part two. The manipulated variables were found to have no significant statistical effect. However, three underlying hypotheses were found to underpin decisions; (a) child rescue, (b) kinship defence and (c) a hedged position on calculation of risk subject to further assessment. Reasoning strategies utilised by social workers to support their decision making suggest that they tend to selectively interpret information either positively or negatively to support pre-existing underlying hypotheses. This finding is in keeping with the literature on 'confirmation bias.' The research further draws attention to the need to incorporate open questions in quantitative studies, to help guard against surface reading of data, which often does not 'speak for itself.'

  4. A psychiatric medication decision support guide for social work practice with pregnant and postpartum women.

    PubMed

    Bentley, Kia J; Price, Sarah Kye; Cummings, Cory R

    2014-10-01

    In their work in human services organizations and community agencies across service sectors, social workers encounter pregnant and postpartum women experiencing mental health challenges. This article offers an evidence-informed Decision Support Guide designed for use by social workers working with pregnant and postpartum women who are struggling with complicated decisions about psychiatric medication use. The guide is built on contemporary notions of health literacy and shared decision making and is informed by three areas: (1) research into the lived experiences of pregnant and postpartum women and health care providers around psychiatric medication decision making, (2) a critical review of existing decision aids, and (3) feedback on the strategy from social work practitioners who work with pregnant and postpartum women. Emphasizing the relational nature of social work in supporting effective health-related decision making, the guide relies on maintaining a collaborative practice milieu and using a decision aid that engages clients in discussions about mental health during and around the time of pregnancy. The guide offers social workers a practice tool to support responsive and compassionate care by embracing their roles in problem solving and decision making, providing emotional and psychosocial support, and making appropriate referrals to prescribers.

  5. Using Group Decision Support Systems in Teaching the Small Group Communication Course.

    ERIC Educational Resources Information Center

    Scott, Craig R.

    The nature of group decision support systems (GDSS), its key advantages, and the experience of using it with several classes help illustrate that this type of computer technology can serve an important function in supplementing instruction of the small group course. The primary purpose of a GDSS is to improve group decision-making and…

  6. Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

    EPA Science Inventory

    Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

  7. Effectiveness of an Electronic Performance Support System on Computer Ethics and Ethical Decision-Making Education

    ERIC Educational Resources Information Center

    Kert, Serhat Bahadir; Uz, Cigdem; Gecu, Zeynep

    2014-01-01

    This study examined the effectiveness of an electronic performance support system (EPSS) on computer ethics education and the ethical decision-making processes. There were five different phases to this ten month study: (1) Writing computer ethics scenarios, (2) Designing a decision-making framework (3) Developing EPSS software (4) Using EPSS in a…

  8. DEVELOPMENT OF A DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN-WATERSHEDS

    EPA Science Inventory

    This paper will present an on-going development of an integrated decision support framework (IDSF) for cost-effective placement of best management practices (BMPs) for managing wet weather flows (WWF) in urban watersheds. This decision tool will facilitate the selection and plac...

  9. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    ERIC Educational Resources Information Center

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

  10. Inter-Rater Reliability of the Illinois Structured Decision Support Protocol

    ERIC Educational Resources Information Center

    Kang, Hyun-Ah; Poertner, John

    2006-01-01

    Objective: The purpose of this study was to determine the level of inter-rater reliability of the Illinois Structured Decision Support Protocol by examining the level of Child Protective Services (CPS) caseworkers' agreement regarding state interventions. The Protocol was designed to guide CPS workers to consistent decisions related to the level…

  11. Decision Support System in the Management of Resource-Sharing Networks.

    ERIC Educational Resources Information Center

    Dubey, Yogendra P.

    1984-01-01

    Reports on emergence of decision support system (DSS) as a practical approach for applying computers and information to problems facing management. Information processing and decision making in organizations, simulation-model-based DSS in management of library resource sharing networks, and a resource-sharing simulation system are highlighted.…

  12. Decision Support Systems (DSSs) For Contaminated Land Management - Gaps And Challenges

    EPA Science Inventory

    A plethora of information is available when considering decision support systems for risk-based management of contaminated land. Broad issues of what is contaminated land, what is a brownfield, and what is remediation are discussed in EU countries and the U.S. Making decisions ...

  13. A decision support system for pre-earthquake planning of lifeline networks

    SciTech Connect

    Liang, J.W.

    1996-12-01

    This paper describes the frame of a decision support system for pre-earthquake planning of gas and water networks. The system is mainly based on the earthquake experiences and lessons from the 1976 Tangshan earthquake. The objective of the system is to offer countermeasures and help make decisions for seismic strengthening, remaking, and upgrading of gas and water networks.

  14. Recycling decision support system: Design and development of a Web-based DSS. Master thesis

    SciTech Connect

    Tettelbach, C.G.

    1997-03-01

    The explosive growth of the World Wide Web creates new opportunities for the development and deployment of Decision Support Systems. No longer restricted by machine-specific limitations, Web-based Decision Support Systems (DSS) provide global access to widely diversified and geographically dispersed users through sharing of data, models, algorithms, and modeling environments. This thesis examines the design and development processes involved in the creation of a Web-based DSS. The Recycling Decision Support System utilizes a rapid prototype and refinement process to create a Web-based system focusing on supporting ordinary people and industrial users in making good decisions for recycling and disposal of household and industrial waste. Through abstraction of details from the specific Web-based DSS design, a generalized framework for supporting decision-making via the WWW is built which supports functionality in education, queries, and analysis of complex problems. An important aspect of this research is the development of a new architecture which conforms to the complexities specific to Web-based Decision Support Systems. Prompted by the additional interactions required for WWW connectivity, this architecture incorporates agents for negotiating transactions between the functional components of a standard DSS.

  15. Assessing environmental conditions of Antarctic footpaths to support management decisions.

    PubMed

    Tejedo, Pablo; Benayas, Javier; Cajiao, Daniela; Albertos, Belén; Lara, Francisco; Pertierra, Luis R; Andrés-Abellán, Manuela; Wic, Consuelo; Luciáñez, Maria José; Enríquez, Natalia; Justel, Ana; Reck, Günther K

    2016-07-15

    Thousands of tourists visit certain Antarctic sites each year, generating a wide variety of environmental impacts. Scientific knowledge of human activities and their impacts can help in the effective design of management measures and impact mitigation. We present a case study from Barrientos Island in which a management measure was originally put in place with the goal of minimizing environmental impacts but resulted in new undesired impacts. Two alternative footpaths used by tourist groups were compared. Both affected extensive moss carpets that cover the middle part of the island and that are very vulnerable to trampling. The first path has been used by tourists and scientists since over a decade and is a marked route that is clearly visible. The second one was created more recently. Several physical and biological indicators were measured in order to assess the environmental conditions for both paths. Some physical variables related to human impact were lower for the first path (e.g. soil penetration resistance and secondary treads), while other biochemical and microbiological variables were higher for the second path (e.g. β-glucosidase and phosphatase activities, soil respiration). Moss communities located along the new path were also more diverse and sensitive to trampling. Soil biota (Collembola) was also more abundant and richer. These data indicate that the decision to adopt the second path did not lead to the reduction of environmental impacts as this path runs over a more vulnerable area with more outstanding biological features (e.g. microbiota activity, flora and soil fauna diversity). In addition, the adoption of a new route effectively doubles the human footprint on the island. We propose using only the original path that is less vulnerable to the impacts of trampling. Finally from this process, we identify several key issues that may be taken into account when carrying out impact assessment and environmental management decision-making in the

  16. Assessing environmental conditions of Antarctic footpaths to support management decisions.

    PubMed

    Tejedo, Pablo; Benayas, Javier; Cajiao, Daniela; Albertos, Belén; Lara, Francisco; Pertierra, Luis R; Andrés-Abellán, Manuela; Wic, Consuelo; Luciáñez, Maria José; Enríquez, Natalia; Justel, Ana; Reck, Günther K

    2016-07-15

    Thousands of tourists visit certain Antarctic sites each year, generating a wide variety of environmental impacts. Scientific knowledge of human activities and their impacts can help in the effective design of management measures and impact mitigation. We present a case study from Barrientos Island in which a management measure was originally put in place with the goal of minimizing environmental impacts but resulted in new undesired impacts. Two alternative footpaths used by tourist groups were compared. Both affected extensive moss carpets that cover the middle part of the island and that are very vulnerable to trampling. The first path has been used by tourists and scientists since over a decade and is a marked route that is clearly visible. The second one was created more recently. Several physical and biological indicators were measured in order to assess the environmental conditions for both paths. Some physical variables related to human impact were lower for the first path (e.g. soil penetration resistance and secondary treads), while other biochemical and microbiological variables were higher for the second path (e.g. β-glucosidase and phosphatase activities, soil respiration). Moss communities located along the new path were also more diverse and sensitive to trampling. Soil biota (Collembola) was also more abundant and richer. These data indicate that the decision to adopt the second path did not lead to the reduction of environmental impacts as this path runs over a more vulnerable area with more outstanding biological features (e.g. microbiota activity, flora and soil fauna diversity). In addition, the adoption of a new route effectively doubles the human footprint on the island. We propose using only the original path that is less vulnerable to the impacts of trampling. Finally from this process, we identify several key issues that may be taken into account when carrying out impact assessment and environmental management decision-making in the

  17. A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

    EPA Science Inventory

    We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environ...

  18. GET SMARTE: A DECISION SUPPORT SYSTEM TO REVITALIZE COMMUNITIES - CABERNET 2007

    EPA Science Inventory

    Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...

  19. The Integrated Medical Model: A Decision Support Tool for In-flight Crew Health Care

    NASA Technical Reports Server (NTRS)

    Butler, Doug

    2009-01-01

    This viewgraph presentation reviews the development of an Integrated Medical Model (IMM) decision support tool for in-flight crew health care safety. Clinical methods, resources, and case scenarios are also addressed.

  20. Framework for securing personal health data in clinical decision support systems.

    PubMed

    Sandell, Protik

    2007-01-01

    If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data.

  1. GREENER CHEMICAL PROCESS DESIGN ALTERNATIVES ARE REVEALED USING THE WASTE REDUCTION DECISION SUPPORT SYSTEM (WAR DSS)

    EPA Science Inventory

    The Waste Reduction Decision Support System (WAR DSS) is a Java-based software product providing comprehensive modeling of potential adverse environmental impacts (PEI) predicted to result from newly designed or redesigned chemical manufacturing processes. The purpose of this so...

  2. Learning interpretive decision algorithm for severe storm forecasting support

    SciTech Connect

    Gaffney, J.E. Jr.; Racer, I.R.

    1983-01-01

    As part of its ongoing program to develop new and better forecasting procedures and techniques, the National Weather Service has initiated an effort in interpretive processing. Investigation has begun to determine the applicability of artificial intelligence (AI)/expert system technology to interpretive processing. This paper presents an expert system algorithm that is being investigated to support the forecasting of severe thunderstorms. 14 references.

  3. [Knowledge management system for laboratory work and clinical decision support].

    PubMed

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.

  4. [Knowledge management system for laboratory work and clinical decision support].

    PubMed

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support

  5. Mathematical Modeling of spatial disease variables by Spatial Fuzzy Logic for Spatial Decision Support Systems

    NASA Astrophysics Data System (ADS)

    Platz, M.; Rapp, J.; Groessler, M.; Niehaus, E.; Babu, A.; Soman, B.

    2014-11-01

    A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.

  6. Computer-based tools for decision support at the Hanford Site

    SciTech Connect

    Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

    1992-11-01

    To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

  7. Computer-based tools for decision support at the Hanford Site

    SciTech Connect

    Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

    1992-11-01

    To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high` level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ``glue`` or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

  8. Decision-support systems for natural-hazards and land-management issues

    USGS Publications Warehouse

    Dinitz, Laura; Forney, William; Byrd, Kristin

    2012-01-01

    Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

  9. An Integrated Web-based Decision Support System in Disaster Risk Management

    NASA Astrophysics Data System (ADS)

    Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

    2012-04-01

    Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact

  10. International online support to process optimisation and operation decisions.

    PubMed

    Onnerth, T B; Eriksson, J

    2002-01-01

    The information level at all technical facilities has developed from almost nothing 30-40 years ago to advanced IT--Information Technology--systems based on both chemical and mechanical on-line sensors for process and equipment. Still the basic part of information is to get the right data at the right time for the decision to be made. Today a large amount of operational data is available at almost any European wastewater treatment plant, from laboratory and SCADA. The difficult part is to determine which data to keep, which to use in calculations and how and where to make data available. With the STARcontrol system it is possible to separate only process relevant data to use for on-line control and reporting at engineering level, to optimise operation. Furthermore, the use of IT makes it possible to communicate internationally, with full access to the whole amount of data on the single plant. In this way, expert supervision can be both very local in local language e.g. Polish and at the same time very professional with Danish experts advising on Danish processes in Poland or Sweden where some of the 12 STARcontrol systems are running. PMID:11936670

  11. Indigenous knowledge as decision support tool in rainwater harvesting

    NASA Astrophysics Data System (ADS)

    Mbilinyi, B. P.; Tumbo, S. D.; Mahoo, H. F.; Senkondo, E. M.; Hatibu, N.

    Rainfall patterns in semi-arid areas are typically highly variable, both spatially and temporally. As a result, people who rely completely on rainwater for their survival have over the centuries developed indigenous knowledge/techniques to harvest rainwater. These traditional water-harvesting systems have been sustainable for centuries. The reason for this is that they are compatible with local lifestyles, local institutional patterns and local social systems. In order to develop sustainable strategies, it is therefore important to take into account of, and learn from, what local people already know and do, and to build on this. This paper explores how indigenous knowledge is used by farmers in the Makanya catchment, Kilimanjaro region, Tanzania to identify potential sites for rainwater harvesting (RWH). The paper draws on participatory research methods including focus group discussions, key informant interviews, field visits and participatory workshops. Initial findings indicate that farmers do hold a substantial amount of knowledge about the resources around them. As there are spatially typical aspects to indigenous knowledge, it could be extrapolated over a wider geographic extent. From the preliminary findings, it is being recommended that geographic information system (GIS) could be an important tool to collect and upscale the utility of diverse indigenous knowledge in the decision-making process.

  12. Prioritization of information using decision support systems for seismic risk in Bucharest city

    NASA Astrophysics Data System (ADS)

    Armas, Iuliana; Gheorghe, Diana

    2014-05-01

    Nowadays, because of the ever increasing volume of information, policymakers are faced with decision making problems. Achieving an objective and suitable decision making may become a challenge. In such situations decision support systems (DSS) have been developed. DSS can assist in the decision making process, offering support on how a decision should be made, rather than what decision should be made (Simon, 1979). This in turn potentially involves a huge number of stakeholders and criteria. Regarding seismic risk, Bucharest City is highly vulnerable (Mandrescu et al., 2007). The aim of this study is to implement a spatial decision support system in order to secure a suitable shelter in case of an earthquake occurrence in the historical centre of Bucharest City. In case of a seismic risk, a shelter is essential for sheltering people who lost their homes or whose homes are in danger of collapsing while people at risk receive first aid in the post-disaster phase. For the present study, the SMCE Module for ILWIS 3.4 was used. The methodology included structuring the problem by creating a decision tree, standardizing and weighting of the criteria. The results showed that the most suitable buildings are Tania Hotel, Hanul lui Manuc, The National Bank of Romania, The Romanian Commercial Bank and The National History Museum.

  13. VisualDecisionLinc: a visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry.

    PubMed

    Mane, Ketan K; Bizon, Chris; Schmitt, Charles; Owen, Phillips; Burchett, Bruce; Pietrobon, Ricardo; Gersing, Kenneth

    2012-02-01

    Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data contained in EHR system are typically accessible only in formats that are not conducive to rapid synthesis and interpretation of therapeutic outcomes. In the time-pressured clinical setting, clinicians faced with large amounts of patient data in formats that are not readily interpretable often feel 'information overload'. Decision support tools that enable rapid access at the point of care to aggregate data on the most effective therapeutic outcomes derived from CER would greatly aid the clinical decision-making process and individualize patient care. In this manuscript, we highlight the role that visual analytics can play in CER-based clinical decision support. We developed a 'VisualDecisionLinc' (VDL) tool prototype that uses visual analytics to provide summarized CER-derived data views to facilitate rapid interpretation of large amounts of data. We highlight the flexibility that visual analytics offers to gain an overview of therapeutic options and outcomes and if needed, to instantly customize the evidence to the needs of the patient or clinician. The VDL tool uses visual analytics to help the clinician evaluate and understand the effectiveness and risk of different therapeutic options for different subpopulations of patients.

  14. Methodical Approach to Developing a Decision Support System for Well Interventions Planning

    NASA Astrophysics Data System (ADS)

    Silich, V. A.; Savelev, A. O.; Isaev, A. N.

    2016-04-01

    The paper contains aspects of developing a decision support systems aimed for well interventions planning within the process of oil production engineering. The specific approach described by authors is based on system analysis methods and object model for system design. Declared number of problem-decision principles as follows: the principle of consolidated information area, the principle of integrated control, the principle of development process transparency. Also observed a set of models (class model, object model, attribute interdependence model, component model, coordination model) specified for designing decision support system for well intervention planning.

  15. Rule-based and information-integration category learning in normal aging.

    PubMed

    Maddox, W Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M

    2010-08-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated processes, whereas information-integration is thought to involve implicit, striatally mediated processes. As a group, older adults showed rule-based and information-integration deficits. A series of models were applied that provided insights onto the type of strategy used to solve the task. Interestingly, when the analyses focused only on participants who used the task appropriate strategy in the final block of trials, the age-related rule-based deficit disappeared whereas the information-integration deficit remained. For this group of individuals, the final block information-integration deficit was due to less consistent application of the task appropriate strategy by older adults, and over the course of learning these older adults shifted from an explicit hypothesis-testing strategy to the task appropriate strategy later in learning. In addition, the use of the task appropriate strategy was associated with less interference and better inhibitory control for rule-based and information-information learning, whereas use of the task appropriate strategy was associated with greater working memory and better new verbal learning only for the rule-based task. These results suggest that normal aging impacts both forms of category learning and that there are some important similarities and differences in the explanatory locus of these deficits. The data also support a two-component model of information-integration category learning that includes a striatal component that mediated procedural-based learning, and a prefrontal cortical component that mediates the transition from hypothesis-testing to procedural-based strategies

  16. A logical model of cooperating rule-based systems

    NASA Technical Reports Server (NTRS)

    Bailin, Sidney C.; Moore, John M.; Hilberg, Robert H.; Murphy, Elizabeth D.; Bahder, Shari A.

    1989-01-01

    A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

  17. Rule-based fault-tolerant flight control

    NASA Technical Reports Server (NTRS)

    Handelman, Dave

    1988-01-01

    Fault tolerance has always been a desirable characteristic of aircraft. The ability to withstand unexpected changes in aircraft configuration has a direct impact on the ability to complete a mission effectively and safely. The possible synergistic effects of combining techniques of modern control theory, statistical hypothesis testing, and artificial intelligence in the attempt to provide failure accommodation for aircraft are investigated. This effort has resulted in the definition of a theory for rule based control and a system for development of such a rule based controller. Although presented here in response to the goal of aircraft fault tolerance, the rule based control technique is applicable to a wide range of complex control problems.

  18. Agricultural climate impacts assessment for economic modeling and decision support

    NASA Astrophysics Data System (ADS)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  19. Decision-support tools for the assessment process

    SciTech Connect

    Whelan, Gene; Pelton, Mitch A.; Dorow, Kevin E.

    2004-06-14

    A new software system is under development that provides a framework to link disparate assessment software and databases for site-specific, regional, or national analyses. This system represents the merger of the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES), which performs site-specific assessments, and Multi-media, Multi-pathway, Multi-receptor Risk Assessment (3MRA) methodology, which performs regional and national assessments. This Merged System is an icon-driven, site-layout platform, which represents an interactive means by which the user graphically constructs a conceptualization of the problem by visually expressing the assessment, indicating sources of contamination, contaminant travel pathways through the environment, linkages between contamination and people or wildlife, and impacts associated with the contamination. It processes data as part of a systems-based assessment and is an open-architecture, object-oriented framework, which contains ''sockets'' for a collection of databases and computer codes that will transparently simulate elements of transport, exposure, and risk assessment, including contaminant source and release to and through overland soils, vadose and saturated zones, air, surface water, food supply, intake human health impacts, sensitivity/uncertainty, ecological impacts, with the ability to expand into areas including Geographical Information System (GIS), remediation technology, cost analysis, Data Quality Objectives, life-cycle management, and conceptual site design. A user can choose from a list of models, and the assessment path forward can be visually presented, which describes the models and their linkages from source through receptor to the decision-making endpoint.

  20. Investigating Habitat Value in Support of Contaminant Remediation Decisions: Approach

    SciTech Connect

    Efroymson, Rebecca Ann; Peterson, Mark J; Welsh, Christopher John Edward; Druckenbrod, Daniel L; Ryon, Michael G; Smith, John G; Hargrove, William Walter; Giffen, Neil R; Roy, W Kelly; Quarles III, Harry Dewitt

    2008-01-01

    Habitat valuation methods are most often developed and used to prioritize candidate lands for conservation. In this study the intent of habitat valuation was to inform the decision-making process for remediation of chemical contaminants on specific lands or surface water bodies. Methods were developed to summarize dimensions of habitat value for six representative aquatic and terrestrial contaminated sites at the East Tennessee Technology Park (ETTP) on the US Department of Energy Oak Ridge Reservation in Oak Ridge, TN, USA. Several general valuation metrics were developed for three broad categories: site use by groups of organisms, site rarity, and use value added from spatial context. Examples of use value metrics are taxa richness, a direct measure of number of species that inhabit an area, complexity of habitat structure, an indirect measure of potential number of species that may use the area, and land use designation, a measure of the length of time that the area will be available for use. Measures of rarity included presence of rare species or communities. Examples of metrics for habitat use value added from spatial context included similarity or complementarity of neighboring habitat patches and presence of habitat corridors. More specific metrics were developed for groups of organisms in contaminated streams, ponds, and terrestrial ecosystems. For each of these metrics, cutoff values for high, medium, and low habitat value were suggested, based on available information on distributions of organisms and landscape features, as well as habitat use information. A companion paper describes the implementation of these habitat valuation metrics and scoring criteria in the remedial investigation for ETTP.

  1. Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

    NASA Astrophysics Data System (ADS)

    Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

    2014-05-01

    Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

  2. Identifying the decision to be supported: a review of papers from environmental modelling and software

    USGS Publications Warehouse

    Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

    2012-01-01

    Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for

  3. Information System Engineering Supporting Observation, Orientation, Decision, and Compliant Action

    NASA Astrophysics Data System (ADS)

    Georgakopoulos, Dimitrios

    The majority of today's software systems and organizational/business structures have been built on the foundation of solving problems via long-term data collection, analysis, and solution design. This traditional approach of solving problems and building corresponding software systems and business processes, falls short in providing the necessary solutions needed to deal with many problems that require agility as the main ingredient of their solution. For example, such agility is needed in responding to an emergency, in military command control, physical security, price-based competition in business, investing in the stock market, video gaming, network monitoring and self-healing, diagnosis in emergency health care, and many other areas that are too numerous to list here. The concept of Observe, Orient, Decide, and Act (OODA) loops is a guiding principal that captures the fundamental issues and approach for engineering information systems that deal with many of these problem areas. However, there are currently few software systems that are capable of supporting OODA. In this talk, we provide a tour of the research issues and state of the art solutions for supporting OODA. In addition, we provide specific examples of OODA solutions we have developed for the video surveillance and emergency response domains.

  4. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation

    PubMed Central

    Linan, Margaret K.; Sottara, Davide; Freimuth, Robert R.

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines. PMID:26958298

  5. Towards an intelligent decision support system for public health surveillance - a qualitative analysis of information needs.

    PubMed

    Mera, Maritza; González, Carolina; López, Diego M

    2014-01-01

    Public health information systems are often implemented considering the functionalities and requirements established by administrative staff or researchers, but sometimes ignoring the particular needs of decision makers. This paper describes a proposal to support the design of a Decision Support System for Public Health Surveillance in Colombia, by conducting a qualitative study to identify the real needs of people involved in decision making processes. Based on the study results, an intelligent computational component that supports Data Analysis Automation, Prediction of future scenarios and the identification of new Behavioral Patterns is proposed. The component will be implemented using the Case Based Reasoning methodology, which will be integrated as a new component of the Open Source DHIS2 Platform, enabling public health decision-making.

  6. Introducing pharmacogenetic testing with clinical decision support into primary care: a feasibility study

    PubMed Central

    Dawes, Martin; Aloise, Martin N.; Ang, J. Sidney; Cullis, Pieter; Dawes, Diana; Fraser, Robert; Liknaitzky, Gideon; Paterson, Andrea; Stanley, Paul; Suarez-Gonzalez, Adriana; Katzov-Eckert, Hagit

    2016-01-01

    Background: Inappropriate prescribing increases patient illness and death owing to adverse drug events. The inclusion of genetic information into primary care medication practices is one solution. Our aim was to assess the ability to obtain and genotype saliva samples and to determine the levels of use of a decision support tool that creates medication options adjusted for patient characteristics, drug-drug interactions and pharmacogenetics. Methods: We conducted a cohort study in 6 primary care settings (5 family practices and 1 pharmacy), enrolling 191 adults with at least 1 of 10 common diseases. Saliva samples were obtained in the physician's office or pharmacy and sent to our laboratory, where DNA was extracted and genotyped and reports were generated. The reports were sent directly to the family physician/pharmacist and linked to an evidence-based prescribing decision support system. The primary outcome was ability to obtain and genotype samples. The secondary outcomes were yield and purity of DNA samples, ability to link results to decision support software and use of the decision support software. Results: Genotyping resulted in linking of 189 patients (99%) with pharmacogenetic reports to the decision support program. A total of 96.8% of samples had at least 1 actionable genotype for medications included in the decision support system. The medication support system was used by the physicians and pharmacists 236 times over 3 months. Interpretation: Physicians and pharmacists can collect saliva samples of sufficient quantity and quality for DNA extraction, purification and genotyping. A clinical decision support system with integrated data from pharmacogenetic tests may enable personalized prescribing within primary care. Trial registration: ClinicalTrials.gov, NCT02383290. PMID:27730116

  7. Evaluating Michigan's community hospital access: spatial methods for decision support

    PubMed Central

    Messina, Joseph P; Shortridge, Ashton M; Groop, Richard E; Varnakovida, Pariwate; Finn, Mark J

    2006-01-01

    approaches enable policymakers to identify under-served areas. Ultimately this paper is concerned with the intersection of spatial analysis and policymaking. Using the best scientific practice to identify locations of under-served populations based on many factors provides policymakers with a powerful tool for making good decisions. PMID:16995948

  8. Geospatial Data Fusion and Multigroup Decision Support for Surface Water Quality Management

    NASA Astrophysics Data System (ADS)

    Sun, A. Y.; Osidele, O.; Green, R. T.; Xie, H.

    2010-12-01

    Social networking and social media have gained significant popularity and brought fundamental changes to many facets of our everyday life. With the ever-increasing adoption of GPS-enabled gadgets and technology, location-based content is likely to play a central role in social networking sites. While location-based content is not new to the geoscience community, where geographic information systems (GIS) are extensively used, the delivery of useful geospatial data to targeted user groups for decision support is new. Decision makers and modelers ought to make more effective use of the new web-based tools to expand the scope of environmental awareness education, public outreach, and stakeholder interaction. Environmental decision processes are often rife with uncertainty and controversy, requiring integration of multiple sources of information and compromises between diverse interests. Fusing of multisource, multiscale environmental data for multigroup decision support is a challenging task. Toward this goal, a multigroup decision support platform should strive to achieve transparency, impartiality, and timely synthesis of information. The latter criterion often constitutes a major technical bottleneck to traditional GIS-based media, featuring large file or image sizes and requiring special processing before web deployment. Many tools and design patterns have appeared in recent years to ease the situation somewhat. In this project, we explore the use of Web 2.0 technologies for “pushing” location-based content to multigroups involved in surface water quality management and decision making. In particular, our granular bottom-up approach facilitates effective delivery of information to most relevant user groups. Our location-based content includes in-situ and remotely sensed data disseminated by NASA and other national and local agencies. Our project is demonstrated for managing the total maximum daily load (TMDL) program in the Arroyo Colorado coastal river basin

  9. Testing an Irrigation Decision Support Tool for California Specialty Crops

    NASA Astrophysics Data System (ADS)

    Johnson, L.; Cahn, M.; Benzen, S.; Zaragoza, I.; Murphy, L.; Melton, F. S.; Martin, F.; Quackenbush, A.; Lockhart, T.

    2015-12-01

    Estimation of crop evapotranspiration supports efficiency of irrigation water management, which in turn can mitigate nitrate leaching, groundwater depletion, and provide energy savings. Past research in California and elsewhere has revealed strong relationships between photosynthetically active vegetation fraction (Fc) and crop evapotranspiration (ETc). Additional research has shown the potential of monitoring Fc by satellite remote sensing. The U.C. Cooperative Extension developed and operates CropManage (CM) as on-line database irrigation (and nitrogen) scheduling tool. CM accounts for the rapid growth and typically brief cycle of cool-season vegetables, where Fc and fraction of reference ET can change daily during canopy development. The model automates crop water requirement calculations based on reference ET data collected by California Dept. Water Resources. Empirically-derived equations are used to estimate daily Fc time-series for a given crop type primarily as a function of planting date and expected harvest date. An application programming interface (API) is under development to provide a check on modeled Fc of current crops and facilitate CM expansion to new crops. The API will enable CM to extract field scale Fc observations from NASA's Satellite Irrigation Management Support (SIMS). SIMS is mainly Landsat based and currently monitors Fc over about 8 million irrigation acres statewide, with potential for adding data from ESA/Sentinel for improved temporal resolution. In the current study, a replicated irrigation trial was performed on romaine lettuce at the USDA Agricultural Research Station in Salinas, CA. CropManage recommendations were used to guide water treatments by drip irrigation at 50%, 75%, 100% ETc replacement levels, with an added treatment at 150% ET representing grower standard practice. Experimental results indicate that yields from the 100% and 150% treatments were not significantly different and were in-line with industry average, while

  10. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    PubMed

    Zhang, Mingyuan; Velasco, Ferdinand T; Musser, R Clayton; Kawamoto, Kensaku

    2013-01-01

    Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale.

  11. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    PubMed

    Zhang, Mingyuan; Velasco, Ferdinand T; Musser, R Clayton; Kawamoto, Kensaku

    2013-01-01

    Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

  12. Personalised Multi-Criterial Online Decision Support for Siblings Considering Stem Cell Donation: An Interactive Aid.

    PubMed

    Kaltoft, Mette Kjer; Salkeld, Glenn; Dowie, Jack

    2016-01-01

    Person-centred decision support combines the best available information on the considerations that matter to the individual, with the importance the person attaches to those considerations. Nurses and other health professionals can benefit from being able to draw on this support within a clinical conversation. A case study and storyline on four siblings facing a transplant coordinator's call to donate stem cells to their brother [1] is 'translated' and used to demonstrate how an interactive multi-criteria aid can be developed for each within a conversational mode. The personalized dialogue and decision aid are accessible online for interaction. Each sibling's decision exemplifies the communication including physical and psychosocial complexities within any decision cascade from call-to-test and to donate, if compatible. A shared template can embrace the informational and ethical aspects of a decision. By interactive decision support within a clinical conversation, each stakeholder can gain a personalised opinion, as well as increased generic health decision literacy [2]. PMID:27332459

  13. An Exploratory Study of Life-Change Events, Social Support and Pregnancy Decisions in Adolescents.

    ERIC Educational Resources Information Center

    Carlson, Mary L.; And Others

    1984-01-01

    Examined influences on decisions regarding pregnancy outcome in 43 adolescents who completed the Adolescent Life Change Event Questionnaire and the Social Support Questionnaire. Those continuing the pregnancy (N=30) had higher life event change scores, lower social support scores, and more personal and family problems. (JAC)

  14. A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

    NASA Astrophysics Data System (ADS)

    Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

    2012-12-01

    We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.

  15. Fuzzy-rule based metamodeling of nitrate transport in large catchments

    NASA Astrophysics Data System (ADS)

    van der Heijden, S.; Haberlandt, U.

    2012-04-01

    Especially for nutrient balance simulations, physically based ecohydrological modeling needs an abundance of measured data and model parameters, which for large catchments all too often are not available in sufficient spatial or temporal resolution or are simply unknown. For efficient large-scale studies it is thus beneficial to have methods at one's disposal which are parsimonious concerning the number of model parameters and the necessary input data. One such method is fuzzy-rule based modeling, which compared to other machine-learning techniques has the advantages to produce models (the fuzzy-rules) which are physically interpretable to a certain extent, and to allow the explicit introduction of expert knowledge through pre-defined rules. The study focuses on the application of fuzzy-rule based modeling for nitrate transport simulation in large catchments, in particular concerning decision support. To be able to construct such models it is possible to take a well-calibrated physically based model to produce data. This metamodeling approach replaces missing observed data. Thus, in a first step the ecohydrological model SWAT was calibrated for a 1000 km2 study area in Northern Germany and used to produce the needed data for rule training. Taking into account the different pathways of nitrate emission from soils (surface runoff, interflow, leaching to groundwater), a modular setup was chosen for the fuzzy model. Two modules were created for each pathway, one for the calculation of fertilized soils and one for non-fertilized soils. Adding one module for groundwater and one for river runoff yields a model consisting of eight modules in total. After selection of appropriate input variables (seven to nine variables for each module) the modules were trained using the SWAT data and simulated annealing as a discrete optimization method. Although flow components are of major importance when describing nitrate transport, they also imply a dependence on (deterministic) water

  16. A Decision Support Framework for Genomically Informed Investigational Cancer Therapy

    PubMed Central

    Johnson, Amber; Holla, Vijaykumar; Bailey, Ann Marie; Brusco, Lauren; Chen, Ken; Routbort, Mark; Patel, Keyur P.; Zeng, Jia; Kopetz, Scott; Davies, Michael A.; Piha-Paul, Sarina A.; Hong, David S.; Eterovic, Agda Karina; Tsimberidou, Apostolia M.; Broaddus, Russell; Bernstam, Elmer V.; Shaw, Kenna R.; Mendelsohn, John; Mills, Gordon B.

    2015-01-01

    Rapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient’s molecular profile, including molecular characterization of the tumor and the patient’s germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a “cancer gene” at the level of a specific variant in order to discriminate so-called “drivers” from “passengers.” Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially “actionable.” At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients. PMID:25863335

  17. Modelling Vague Knowledge for Decision Support in Planning Archaeological Prospections

    NASA Astrophysics Data System (ADS)

    Boos, S.; Hornung, S.; Müller, H.

    2012-07-01

    Most archaeological predictive models lack significance because fuzziness of data and uncertainty in knowledge about human behaviour and natural processes are hardly ever considered. One possibility to cope with such uncertainties is utilization of probability based approaches like Bayes Theorem or Dempster-Shafer-Theory. We analyzed an area of 50 km2 in Rhineland Palatinate (Germany) near a Celtic oppidum by use of Dempster-Shafer's theory of evidence for predicting spatial probability distribution of archaeological sites. This technique incorporates uncertainty by assigning various weights of evidence to defined variables, in that way estimating the probability for supporting a specific hypothesis (in our case the hypothesis presence or absence of a site). Selection of variables for our model relied both on assumptions about settlement patterns and on statistically tested relationships between known archaeological sites and environmental factors. The modelling process was conducted in a Geographic Information System (GIS) by generating raster-based likelihood surfaces. The corresponding likelihood surfaces were aggregated to a final weight of evidence surface, which resulted in a likelihood value for every single cell of being a site or a non-site. Finally the result was tested against a database of known archaeological sites for evaluating the gain of the model. For the purpose of enhancing the gain of our model and sharpening our criteria we used a two-step approach to improve the modelling of former settlement strategies in our study area. Applying the developed model finally yielded a 100 percent success rate of known archaeological sites located in predicted high potential areas.

  18. Quantitative ultrasound texture analysis for clinical decision making support

    NASA Astrophysics Data System (ADS)

    Wu, Jie Ying; Beland, Michael; Konrad, Joseph; Tuomi, Adam; Glidden, David; Grand, David; Merck, Derek

    2015-03-01

    We propose a general ultrasound (US) texture-analysis and machine-learning framework for detecting the presence of disease that is suitable for clinical application across clinicians, disease types, devices, and operators. Its stages are image selection, image filtering, ROI selection, feature parameterization, and classification. Each stage is modular and can be replaced with alternate methods. Thus, this framework is adaptable to a wide range of tasks. Our two preliminary clinical targets are hepatic steatosis and adenomyosis diagnosis. For steatosis, we collected US images from 288 patients and their pathology-determined values of steatosis (%) from biopsies. Two radiologists independently reviewed all images and identified the region of interest (ROI) most representative of the hepatic echotexture for each patient. To parameterize the images into comparable quantities, we filter the US images at multiple scales for various texture responses. For each response, we collect a histogram of pixel features within the ROI, and parameterize it as a Gaussian function using its mean, standard deviation, kurtosis, and skew to create a 36-feature vector. Our algorithm uses a support vector machine (SVM) for classification. Using a threshold of 10%, we achieved 72.81% overall accuracy, 76.18% sensitivity, and 65.96% specificity in identifying steatosis with leave-ten-out cross-validation (p<0.0001). Extending this framework to adenomyosis, we identified 38 patients with MR-confirmed findings of adenomyosis and previous US studies and 50 controls. A single rater picked the best US-image and ROI for each case. Using the same processing pipeline, we obtained 76.14% accuracy, 86.00% sensitivity, and 63.16% specificity with leave-one-out cross-validation (p<0.0001).

  19. A fuzzy rule based framework for noise annoyance modeling.

    PubMed

    Botteldooren, Dick; Verkeyn, Andy; Lercher, Peter

    2003-09-01

    Predicting the effect of noise on individual people and small groups is an extremely difficult task due to the influence of a multitude of factors that vary from person to person and from context to context. Moreover, noise annoyance is inherently a vague concept. That is why, in this paper, it is argued that noise annoyance models should identify a fuzzy set of possible effects rather than seek a very accurate crisp prediction. Fuzzy rule based models seem ideal candidates for this task. This paper provides the theoretical background for building these models. Existing empirical knowledge is used to extract a few typical rules that allow making the model more specific for small groups of individuals. The resulting model is tested on two large-scale social surveys augmented with exposure simulations. The testing demonstrates how this new way of thinking about noise effect modeling can be used in practice both in management support as a "noise annoyance adviser" and in social science for testing hypotheses such as the effect of noise sensitivity or the degree of urbanization.

  20. A rule based computer aided design system

    NASA Technical Reports Server (NTRS)

    Premack, T.

    1986-01-01

    A Computer Aided Design (CAD) system is presented which supports the iterative process of design, the dimensional continuity between mating parts, and the hierarchical structure of the parts in their assembled configuration. Prolog, an interactive logic programming language, is used to represent and interpret the data base. The solid geometry representing the parts is defined in parameterized form using the swept volume method. The system is demonstrated with a design of a spring piston.

  1. Rule-based Cross-matching of Very Large Catalogs

    NASA Astrophysics Data System (ADS)

    Ogle, P. M.; Mazzarella, J.; Ebert, R.; Fadda, D.; Lo, T.; Terek, S.; Schmitz, M.; NED Team

    2015-09-01

    The NASA Extragalactic Database (NED) has deployed a new rule-based cross-matching algorithm called Match Expert (MatchEx), capable of cross-matching very large catalogs (VLCs) with >10 million objects. MatchEx goes beyond traditional position-based cross-matching algorithms by using other available data together with expert logic to determine which candidate match is the best. Furthermore, the local background density of sources is used to determine and minimize the false-positive match rate and to estimate match completeness. The logical outcome and statistical probability of each match decision is stored in the database and may be used to tune the algorithm and adjust match parameter thresholds. For our first production run, we cross-matched the GALEX All Sky Survey Catalog (GASC), containing nearly 40 million NUV-detected sources, against a directory of 180 million objects in NED. Candidate matches were identified for each GASC source within a 7''.5 radius. These candidates were filtered on position-based matching probability and on other criteria including object type and object name. We estimate a match completeness of 97.6% and a match accuracy of 99.75%. Over the next year, we will be cross-matching over 2 billion catalog sources to NED, including the Spitzer Source List, the 2MASS point-source catalog, AllWISE, and SDSS DR 10. We expect to add new capabilities to filter candidate matches based on photometry, redshifts, and refined object classifications. We will also extend MatchEx to handle more heterogenous datasets federated from smaller catalogs through NED's literature pipeline.

  2. Use of Simulation to Study Nurses' Acceptance and Nonacceptance of Clinical Decision Support Suggestions.

    PubMed

    Sousa, Vanessa E C; Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Yao, Yingwei; Johnson, Andrew; Wilkie, Diana J; Keenan, Gail M

    2015-10-01

    Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice. PMID:26361268

  3. Decision support systems in water and wastewater treatment process selection and design: a review.

    PubMed

    Hamouda, M A; Anderson, W B; Huck, P M

    2009-01-01

    The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach. PMID:19809138

  4. The application of decision analysis to life support research and technology development

    NASA Technical Reports Server (NTRS)

    Ballin, Mark G.

    1994-01-01

    Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

  5. Fuzzy Cognitive Map scenario-based medical decision support systems for education.

    PubMed

    Georgopoulos, Voula C; Chouliara, Spyridoula; Stylios, Chrysostomos D

    2014-01-01

    Soft Computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if" scenarios in case studies and prepare for dealing with critical adverse events.

  6. NASA's past, current and potential future support in bringing climate projection information to the decision support level

    NASA Astrophysics Data System (ADS)

    Lee, T. J.

    2015-12-01

    It is common that we use global climate models or Earth system models to perform climate projection into the future. Because of the long integration time and the tremendous computing resources required for such a projection, the model resolution is typically not at a spatial scale fine enough for climate assessment or decision support purposes. A number of "downscaling technologies" have been developed over the years to bring the climate projection information to the local level for management and policy decision support purposes. In the past couple of years, NASA supported a number of regional to local climate projection activities: NASA Climate Adaption Science Investigators focused on climate resilience at NASA center level, National Climate Assessment (NCA) Capacity Building focused on data sets and tools to support NCA, NCA Indicators focused on creating simple indicators specifically designed for decision support, Assessing the Fidelity of Dynamical Downscaling with the NASA Unifies-WRF Model focused on understanding the credibility of dynamical downscaling technique using a regional climate model. All of these projects have a component in creating or using downscaled climate information. With the consequence of climate change beginning to emerge, there is a continuous need to better quantify the quality of downscaled climate projections. In this talk I will give an overview on NASA's efforts to understand the various techniques, the limitations including the risks of using these techniques, and finally, I will provide a view on possible future researches in this area.

  7. Design of decision support system when undertaking medical-diagnostic action

    NASA Astrophysics Data System (ADS)

    Povoroznyuk, Anatoliy I.; Filatova, Anna E.; Surtel, Wojciech; Burlibay, Aron; Zhassandykyzy, Maral

    2015-12-01

    In the work the formalization of the problem of diagnostic and treatment activities (DTA) steps complex estimation for increasing of their efficiency and minimization of the risk of doctor's mistakes was completed. The decision support system during conducting of DTA based on formalizations of steps of DTA performing with theirs complex estimation was developed that allows to minimize the risks of doctor's mistakes, raise validity of decisions.

  8. Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

    PubMed

    Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

    2005-06-01

    This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.

  9. Association-rule-based tuberculosis disease diagnosis

    NASA Astrophysics Data System (ADS)

    Asha, T.; Natarajan, S.; Murthy, K. N. B.

    2010-02-01

    Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air and attacks low immune bodies such as patients with Human Immunodeficiency Virus (HIV). This work focuses on finding close association rules, a promising technique in Data Mining, within TB data. The proposed method first normalizes of raw data from medical records which includes categorical, nominal and continuous attributes and then determines Association Rules from the normalized data with different support and confidence. Association rules are applied on a real data set containing medical records of patients with TB obtained from a state hospital. The rules determined describes close association between one symptom to another; as an example, likelihood that an occurrence of sputum is closely associated with blood cough and HIV.

  10. Secure Medical Diagnosis Using Rule Based Mining

    NASA Astrophysics Data System (ADS)

    Saleem Durai, M. A.; Sriman Narayana Iyengar, N. Ch.

    Security is the governing dynamics of all walks of life. Here we propose a secured medical diagnosis system. Certain specific rules are specified implicitly by the designer of the expert system and then symptoms for the diseases are obtained from the users and by using the pre defined confidence and support values we extract a threshold value which is used to conclude on a particular disease and the stage using Rule Mining. "THINK" CAPTCHA mechanism is used to distinguish between the human and the robots thereby eliminating the robots and preventing them from creating fake accounts and spam's. A novel image encryption mechanism is designed using genetic algorithm to encrypt the medical images thereby storing and sending the image data in a secured manner.

  11. Risk-based decision support tools: protecting rail-centered transit corridors from cascading effects.

    PubMed

    Greenberg, Michael R; Lowrie, Karen; Mayer, Henry; Altiok, Tayfur

    2011-12-01

    We consider the value of decision support tools for passenger rail system managers. First, we call for models that follow events along main rail lines and then into the surrounding environment where they can cascade onto connected light rail, bus, auto, truck, and other transport modes. Second, we suggest that both probabilistic risk assessment (PRA-based) and agent-based models have a role to play at different scales of analysis and for different kinds of risks. Third, we argue that economic impact tools need more systematic evaluation. Fourth, we note that developers of decision support tools face a challenge of balancing their desire for theoretical elegance and the tendency to focus only on high consequence events against decisionmakers' mistrust of complex tools that they and their staff cannot manage and incorporate into their routine operations, as well as the high costs of developing, updating, and applying decision support tools to transport systems undergoing budget cuts and worker and service reductions.

  12. Employing clinical decision support to attain our strategic goal: the safe care of the surgical patient.

    PubMed

    Magid, Steven K; Pancoast, Paul E; Fields, Theodore; Bradley, Diane G; Williams, Robert B

    2007-01-01

    Clinical decision support can be employed to increase patient safety and improve workflow efficiencies for physicians and other healthcare providers. Physician input into the design and deployment of clinical decision support systems can increase the utility of the alerts and reduce the likelihood of "alert fatigue." The Hospital for Special Surgery is a 146-bed orthopedic facility that performs approximately 18,000 surgeries a year Efficient work processes are a necessity. The facility began implementing a new electronic health record system in June 2005 and plan to go live in summer 2007. This article reports on some of the clinical decision support rules and alerts being incorporated into the facility's system in the following categories--high-risk, high-frequency scenarios, rules that provide efficiencies and value from the presciber perspective, and rules that relate to patient safety. PMID:17583164

  13. Designing Tools for Supporting User Decision-Making in e-Commerce

    NASA Astrophysics Data System (ADS)

    Sutcliffe, Alistair; Al-Qaed, Faisal

    The paper describes a set of tools designed to support a variety of user decision-making strategies. The tools are complemented by an online advisor so they can be adapted to different domains and users can be guided to adopt appropriate tools for different choices in e-commerce, e.g. purchasing high-value products, exploring product fit to users’ needs, or selecting products which satisfy requirements. The tools range from simple recommenders to decision support by interactive querying and comparison matrices. They were evaluated in a scenario-based experiment which varied the users’ task and motivation, with and without an advisor agent. The results show the tools and advisor were effective in supporting users and agreed with the predictions of ADM (adaptive decision making) theory, on which the design of the tools was based.

  14. Tablet-based patient monitoring and decision support systems in hospital care.

    PubMed

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Linden, Maria

    2015-08-01

    Remote patient monitoring with evidence-based decision support is revolutionizing healthcare. This novel approach could enable both patients and healthcare providers to improve quality of care and reduce costs. Clinicians can also view patients' data within the hospital network on tablet computers as well as other ubiquitous devices. Today, a wide range of applications are available on tablet computers which are increasingly integrating into the healthcare mainstream as clinical decision support systems. Despite the benefits of tablet-based healthcare applications, there are concerns around the accuracy, security and stability of such applications. In this study, we developed five tablet-based application screens for remote patient monitoring at hospital care settings and identified related issues and challenges. The ultimate aim of this research is to integrate decision support algorithms into the monitoring system in order to improve inpatient care and the effectiveness of such applications. PMID:26736485

  15. The potential for meta-analysis to support decision analysis in ecology.

    PubMed

    Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

    2015-06-01

    Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty.

  16. Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

    USGS Publications Warehouse

    Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

    2006-01-01

    There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

  17. A decision support system for map projections of small scale data

    USGS Publications Warehouse

    Finn, Michael P.; Usery, E. Lynn; Posch, Stephan T.; Seong, Jeong Chang

    2004-01-01

    The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

  18. Designing a decision support system for distinguishing ADHD from similar children behavioral disorders.

    PubMed

    Delavarian, Mona; Towhidkhah, Farzad; Dibajnia, Parvin; Gharibzadeh, Shahriar

    2012-06-01

    In this study, a decision support system was designed to distinguish children with ADHD from other similar children behavioral disorders such as depression, anxiety, comorbid depression and anxiety and conduct disorder based on the signs and symptoms. Accuracy of classifying with Radial basis function and multilayer neural networks were compared. Finally, the average accuracy of the networks in classification reached to 95.50% and 96.62% by multilayer and radial basis function networks respectively. Our results indicate that a decision support system, especially RBF, may be a good preliminary assistant for psychiatrists in diagnosing high risk behavioral disorders of children.

  19. IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

    NASA Astrophysics Data System (ADS)

    Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

    2013-04-01

    A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

  20. Supplementing Global Narratives with National to Regional Scale Scenarios for Decision Support (Invited)

    NASA Astrophysics Data System (ADS)

    Moss, R. H.; Patwardhan, A.

    2013-12-01

    This presentation examines decision-making contexts to clarify how globally-oriented scenarios of future demographic, economic, and social conditions (the Shared Socioeconomic Pathways -- SSPs) can be extended or nested with scenarios that are targeted on uncertainties of more immediate concern to decision makers. A number of use cases are explored to identify key uncertainties and the attributes of scenarios that would help decision-makers think through the implications of these uncertainties. These uncertainties concern future conditions at national to regional spatial and governance scales regarding factors outside the locus of control of the decision makers. The exogenous factors that need to be represented in scenarios affect supply and demand of relevant commodities/products, institutional conditions, and vulnerability. They include: demographics & societal conditions; economic growth; policy and institutional context (including public & private responses); technology/resource price and performance; and climate/environmental outcomes. The presentation will explore development of decision-support oriented scenarios that are built from the 'bottom-up' and highlight points of divergence in national/regional social and economic conditions. The authors draw preliminary conclusions regarding methods for nesting decision support scenarios in high-level global narratives.

  1. Translational Cognition for Decision Support in Critical Care Environments: A Review

    PubMed Central

    Patel, Vimla L.; Zhang, Jiajie; Yoskowitz, Nicole A.; Green, Robert; Sayan, Osman R.

    2008-01-01

    The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers. PMID:18343731

  2. Getting the Balance Right: Conceptual Considerations Concerning Legal Capacity and Supported Decision-Making.

    PubMed

    Parker, Malcolm

    2016-09-01

    The United Nations Convention on the Rights of Persons with Disabilities urges and requires changes to how signatories discharge their duties to people with intellectual disabilities, in the direction of their greater recognition as legal persons with expanded decision-making rights. Australian jurisdictions are currently undertaking inquiries and pilot projects that explore how these imperatives should be implemented. One of the important changes advocated is to move from guardianship models to supported or assisted models of decision-making. A driving force behind these developments is a strong allegiance to the social model of disability, in the formulation of the Convention, in inquiries and pilot projects, in implementation and in the related academic literature. Many of these instances suffer from confusing and misleading statements and conceptual misinterpretations of certain elements such as legal capacity, decision-making capacity, and support for decision-making. This paper analyses some of these confusions and their possible negative implications for supported decision-making instruments and those whose interests these instruments would serve, and advises a more incremental development of existing guardianship regimes. This provides a more realistic balance between neglecting the real limits of those with mental disabilities and thereby ignoring their identity and particularity, and continuing to bring them equally and fully into society.

  3. Foundations for context-aware information retrieval for proactive decision support

    NASA Astrophysics Data System (ADS)

    Mittu, Ranjeev; Lin, Jessica; Li, Qingzhe; Gao, Yifeng; Rangwala, Huzefa; Shargo, Peter; Robinson, Joshua; Rose, Carolyn; Tunison, Paul; Turek, Matt; Thomas, Stephen; Hanselman, Phil

    2016-05-01

    Intelligence analysts and military decision makers are faced with an onslaught of information. From the now ubiquitous presence of intelligence, surveillance, and reconnaissance (ISR) platforms providing large volumes of sensor data, to vast amounts of open source data in the form of news reports, blog postings, or social media postings, the amount of information available to a modern decision maker is staggering. Whether tasked with leading a military campaign or providing support for a humanitarian mission, being able to make sense of all the information available is a challenge. Due to the volume and velocity of this data, automated tools are required to help support reasoned, human decisions. In this paper we describe several automated techniques that are targeted at supporting decision making. Our approaches include modeling the kinematics of moving targets as motifs; developing normalcy models and detecting anomalies in kinematic data; automatically classifying the roles of users in social media; and modeling geo-spatial regions based on the behavior that takes place in them. These techniques cover a wide-range of potential decision maker needs.

  4. Developing and validating a practical decision support tool (DST) for biomass selection on marginal land.

    PubMed

    Andersson-Sköld, Y; Bardos, P; Chalot, M; Bert, V; Crutu, G; Phanthavongsa, P; Delplanque, M; Track, T; Cundy, A B

    2014-12-01

    Marginal, often contaminated, sites exist in large areas across the world as a result of historic activities such as industry, transportation and mineral extraction. Remediation, or other improvements, of these sites is typically only considered for sites with high exploitation pressure and those posing the highest risks to human health or the environment. At the same time there is increasing competition for land resources for different needs such as biofuel production. Potentially some of this land requirement could be met by production of biomass on brownfield or other marginal land, thereby improving the land while applying the crop cultivation as part of an integrated management strategy. The design and decision making for such a strategy will be site specific. A decision support framework, the Rejuvenate DST (decision support tool) has been developed with the aim of supporting such site specific decision making. This tool is presented here, and has been tested by applying it to a number of case study sites. The consequent SWOT (strength, weakness, opportunities and threats) analysis is discussed and evaluated. The DST was found to be systematic, transparent, and applicable for diverse sites in France, Romania and Sweden, in addition to the sites to which it was applied through its development. The DST is regarded as especially useful if applied as a checklist in an iterative way throughout the decision process, from identifying potential crops to identifying knowledge gaps, working/non-working management strategies and potential risks. The DST also provides a structure promoting effective stakeholder engagement. PMID:25014888

  5. Developing and validating a practical decision support tool (DST) for biomass selection on marginal land.

    PubMed

    Andersson-Sköld, Y; Bardos, P; Chalot, M; Bert, V; Crutu, G; Phanthavongsa, P; Delplanque, M; Track, T; Cundy, A B

    2014-12-01

    Marginal, often contaminated, sites exist in large areas across the world as a result of historic activities such as industry, transportation and mineral extraction. Remediation, or other improvements, of these sites is typically only considered for sites with high exploitation pressure and those posing the highest risks to human health or the environment. At the same time there is increasing competition for land resources for different needs such as biofuel production. Potentially some of this land requirement could be met by production of biomass on brownfield or other marginal land, thereby improving the land while applying the crop cultivation as part of an integrated management strategy. The design and decision making for such a strategy will be site specific. A decision support framework, the Rejuvenate DST (decision support tool) has been developed with the aim of supporting such site specific decision making. This tool is presented here, and has been tested by applying it to a number of case study sites. The consequent SWOT (strength, weakness, opportunities and threats) analysis is discussed and evaluated. The DST was found to be systematic, transparent, and applicable for diverse sites in France, Romania and Sweden, in addition to the sites to which it was applied through its development. The DST is regarded as especially useful if applied as a checklist in an iterative way throughout the decision process, from identifying potential crops to identifying knowledge gaps, working/non-working management strategies and potential risks. The DST also provides a structure promoting effective stakeholder engagement.

  6. Quality of Online Information to Support Patient Decision-Making in Breast Cancer Surgery

    PubMed Central

    Bruce, Jordan G.; Tucholka, Jennifer L.; Steffens, Nicole M.; Neuman, Heather B.

    2015-01-01

    Background Breast cancer patients commonly use the internet as an information resource. Our objective was to evaluate the quality of online information available to support patients facing a decision for breast surgery. Methods Breast cancer surgery-related queries were performed (Google and Bing), and reviewed for content pertinent to breast cancer surgery. The DISCERN instrument was used to evaluate websites’ structural components that influence publication reliability and ability of information to support treatment decision-making. Scores of 4/5 were considered “good”. Results 45 unique websites were identified. Websites satisfied a median 5/9 content questions. Commonly omitted topics included: having a choice between breast conservation and mastectomy (67%) and potential for 2nd surgery to obtain negative margins after breast conservation (60%). Websites had a median DISCERN score of 2.9 (range 2.0–4.5). Websites achieved higher scores on structural criteria (median 3.6 [2.1–4.7]), with 24% rated as “good”. Scores on supporting decision-making questions were lower (2.6 [1.3–4.4]), with only 7% scoring “good”. Conclusion Although numerous breast cancer-related websites exist, most do a poor job providing women with essential information necessary to actively participate in decision-making for breast cancer surgery. Providing easily-accessible, high-quality online information has the potential to significantly improve patients’ experiences with decision-making. PMID:26417898

  7. From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement.

    PubMed

    Hsueh, Pei-Yun; Lan, Ci-Wei; Deng, Vincent; Zhu, Xinxin

    2012-01-01

    Personalized wellness decision support has gained significant attention, owing to the shift to a patient-centric paradigm in healthcare domains, and the consequent availability of a wealth of patient-related data. Despite the success of data-driven analytics in improving practice outcome, there is a gap towards their deployment in guideline-based practice. In this paper we report on findings related to computer-supported guideline refinement, which maps a patient's guideline requirements to personalized recommendations that suit the patient's current context. In particular, we present a novel data-driven personalization framework, casting the mapping task as a statistical decision problem in search of a solution to maximize expected utility. The proposed framework is well suited to produce personalized recommendations based on not only clinical factors but contextual factors that reflect individual differences in non-clinical settings. We then describe its implementation within the guideline-based clinical decision support system and discuss opportunities and challenges looking forward. PMID:22874232

  8. Toward a multi-objective decision support framework to support regulations of unconventional oil and gas development

    NASA Astrophysics Data System (ADS)

    Alongi, M.; Howard, C.; Kasprzyk, J. R.; Ryan, J. N.

    2015-12-01

    Unconventional oil and gas development (UOGD) using hydraulic fracturing and horizontal drilling has recently fostered an unprecedented acceleration in energy development. Regulations seek to protect environmental quality of areas surrounding UOGD, while maintaining economic benefits. One such regulation is a setback distance, which dictates the minimum proximity between an oil and gas well and an object such as a residential or commercial building, property line, or water source. In general, most setback regulations have been strongly politically motivated without a clear scientific basis for understanding the relationship between the setback distance and various performance outcomes. This presentation discusses a new decision support framework for setback regulations, as part of a large NSF-funded sustainability research network (SRN) on UOGD. The goal of the decision support framework is to integrate a wide array of scientific information from the SRN into a coherent framework that can help inform policy regarding UOGD. The decision support framework employs multiobjective evolutionary algorithm (MOEA) optimization coupled with simulation models of air quality and other performance-based outcomes on UOGD. The result of the MOEA optimization runs are quantitative tradeoff curves among different objectives. For example, one such curve could demonstrate air pollution concentrations versus estimates of energy development profits, for different levels of setback distance. Our results will also inform policy-relevant discussions surrounding UOGD such as comparing single- and multi-well pads, as well as regulations on the density of well development over a spatial area.

  9. From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement.

    PubMed

    Hsueh, Pei-Yun; Lan, Ci-Wei; Deng, Vincent; Zhu, Xinxin

    2012-01-01

    Personalized wellness decision support has gained significant attention, owing to the shift to a patient-centric paradigm in healthcare domains, and the consequent availability of a wealth of patient-related data. Despite the success of data-driven analytics in improving practice outcome, there is a gap towards their deployment in guideline-based practice. In this paper we report on findings related to computer-supported guideline refinement, which maps a patient's guideline requirements to personalized recommendations that suit the patient's current context. In particular, we present a novel data-driven personalization framework, casting the mapping task as a statistical decision problem in search of a solution to maximize expected utility. The proposed framework is well suited to produce personalized recommendations based on not only clinical factors but contextual factors that reflect individual differences in non-clinical settings. We then describe its implementation within the guideline-based clinical decision support system and discuss opportunities and challenges looking forward.

  10. A category-free neural population supports evolving demands during decision-making.

    PubMed

    Raposo, David; Kaufman, Matthew T; Churchland, Anne K

    2014-12-01

    The posterior parietal cortex (PPC) receives diverse inputs and is involved in a dizzying array of behaviors. These many behaviors could rely on distinct categories of neurons specialized to represent particular variables or could rely on a single population of PPC neurons that is leveraged in different ways. To distinguish these possibilities, we evaluated rat PPC neurons recorded during multisensory decisions. Newly designed tests revealed that task parameters and temporal response features were distributed randomly across neurons, without evidence of categories. This suggests that PPC neurons constitute a dynamic network that is decoded according to the animal's present needs. To test for an additional signature of a dynamic network, we compared moments when behavioral demands differed: decision and movement. Our new state-space analysis revealed that the network explored different dimensions during decision and movement. These observations suggest that a single network of neurons can support the evolving behavioral demands of decision-making. PMID:25383902

  11. Breast cancer therapy planning - a novel support concept for a sequential decision making problem.

    PubMed

    Scherrer, Alexander; Schwidde, Ilka; Dinges, Andreas; Rüdiger, Patrick; Kümmel, Sherko; Küfer, Karl-Heinz

    2015-09-01

    Breast cancer is the most common carcinosis with the largest number of mortalities in women. Its therapy comprises a wide spectrum of different treatment modalities a breast oncologist decides about for the individual patient case. These decisions happen according to medical guide lines, current scientific publications and experiences acquired in former cases. Clinical decision making therefore involves the time-consuming search for possible therapy options and their thorough testing for applicability to the current patient case.This research work addresses breast cancer therapy planning as a multi-criteria sequential decision making problem. The approach is based on a data model for patient cases with therapy descriptions and a mathematical notion for therapeutic relevance of medical information. This formulation allows for a novel decision support concept, which targets at eliminating observed weaknesses in clinical routine of breast cancer therapy planning.

  12. Ecosystem services: Challenges and opportunities for hydrologic modeling to support decision making

    NASA Astrophysics Data System (ADS)

    Guswa, Andrew J.; Brauman, Kate A.; Brown, Casey; Hamel, Perrine; Keeler, Bonnie L.; Sayre, Susan Stratton

    2014-05-01

    Ecosystem characteristics and processes provide significant value to human health and well-being, and there is growing interest in quantifying those values. Of particular interest are water-related ecosystem services and the incorporation of their value into local and regional decision making. This presents multiple challenges and opportunities to the hydrologic-modeling community. To motivate advances in water-resources research, we first present three common decision contexts that draw upon an ecosystem-service framework: scenario analysis, payments for watershed services, and spatial planning. Within these contexts, we highlight the particular challenges to hydrologic modeling, and then present a set of opportunities that arise from ecosystem-service decisions. The paper concludes with a set of recommendations regarding how we can prioritize our work to support decisions based on ecosystem-service valuation.

  13. Determining location and size of medical departments in a hospital network: a multiobjective decision support approach.

    PubMed

    Stummer, Christian; Doerner, Karl; Focke, Axel; Heidenberger, Kurt

    2004-02-01

    Decisions on the location and size of medical departments in a given hospital network are prime examples of priority setting in health care, which is an issue of growing political importance. As such decisions are regularly characterized by multiple and often conflicting objectives in real-life, this paper integrates the fields of hospital planning and multiobjective decision support. The proposed two-phase solution procedure for our corresponding mathematical programming model does not require a priori preference information. Instead, it seeks efficient solutions by means of multiobjective tabu search in the first phase, while applying clustering in the second phase to allow the decision makers to interactively explore the solution space until the "best" configuration is determined. The real-world applicability of our approach is illustrated through a numerical example based on hospital data from Germany. PMID:14977095

  14. A Decision Making Methodology in Support of the Business Rules Lifecycle

    NASA Technical Reports Server (NTRS)

    Wild, Christopher; Rosca, Daniela

    1998-01-01

    The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.

  15. [DECIDE: developing and evaluating communication strategies to support informed decisions and practice based on evidence].

    PubMed

    Parmelli, Elena; Amato, Laura; Saitto, Carlo; Davoli, Marina

    2013-10-01

    Healthcare systems are offered with a wide range of technologies and services, but they have to cope with decreasing resources and the uncertainty about what is effective and more appropriate. Making decisions about health care interventions is complex. Decisions should be informed by the best available evidence, being comprehensive to take into account all the relevant aspects (e.g. efficacy, safety, equity, costs), and taken within a limited time period. DECIDE is a project funded by the European Community that, using the GRADE methodology, aims at implementing strategies to enhance dissemination and communication of scientific evidence to support on-time evidence-based decision making in clinical practice and healthcare policies. Communication strategies are developed in order to address different target audiences, trying to meet their information needs. One key target are policy makers and managers who are responsible for coverage decision making. PMID:24326703

  16. A Legal Framework to Enable Sharing of Clinical Decision Support Knowledge and Services across Institutional Boundaries

    PubMed Central

    Hongsermeier, Tonya; Maviglia, Saverio; Tsurikova, Lana; Bogaty, Dan; Rocha, Roberto A.; Goldberg, Howard; Meltzer, Seth; Middleton, Blackford

    2011-01-01

    The goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology at scale – across multiple ambulatory care settings and Electronic Health Record technology platforms. In the course of the CDSC research effort, it became evident that a sound legal foundation was required for knowledge sharing and clinical decision support services in order to address data sharing, intellectual property, accountability, and liability concerns. This paper outlines the framework utilized for developing agreements in support of sharing, accessing, and publishing content via the CDSC Knowledge Management Portal as well as an agreement in support of deployment and consumption of CDSC developed web services in the context of a research project under IRB oversight. PMID:22195151

  17. Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

    PubMed Central

    2014-01-01

    Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health

  18. Requiring Clinical Justification to Override Repeat Imaging Decision Support: Impact on CT Use

    PubMed Central

    O’Connor, Stacy D.; Sodickson, Aaron D.; Ip, Ivan K.; Raja, Ali S.; Healey, Michael J.; Schneider, Louise I.; Khorasani, Ramin

    2014-01-01

    OBJECTIVE The purpose of this study was to determine the impact of requiring clinical justification to override decision support alerts on repeat use of CT. SUBJECTS AND METHODS This before and after intervention study was conducted at a 793-bed tertiary hospital with computerized physician order entry and clinical decision support systems. When a CT order is placed, decision support alerts the orderer if the patient’s same body part has undergone CT within the past 90 days. The study cohort included all 28,420 CT orders triggering a repeat alert in 2010. The intervention required clinical justification, selected from a predetermined menu, to override repeat CT decision support alerts to place a CT order; otherwise the order could not be placed and was dropped. The primary outcome, dropped repeat CT orders, was analyzed using three methods: chi-square tests to compare proportions dropped before and after intervention; multiple logistic regression tests to control for orderer, care setting, and patient factors; and statistical process control for temporal trends. RESULTS The repeat CT order drop rate had an absolute increase of 1.4%; 6.1% (682/11,230) before to 7.5% (1290/17,190) after intervention, which was a 23% relative change (7.5 – 6.1) / 6.1 × 100 = 23%; p < 0.0001). Orders were dropped more often after intervention (odds ratio, 1.3; 95% CI, 1.1–1.4; p < 0.0001). Statistical control analysis supported the association between the increase in the drop rate with intervention rather than underlying trends. CONCLUSION Adding a requirement for clinical justification to override alerts modestly but significantly improves the impact of repeat CT decision support (23% relative change), with the overall effect of preventing one in 13 repeat CT orders. PMID:25341162

  19. Development and application of the decision support system for municipal solid waste management in central Taiwan.

    PubMed

    Chang, Yao-Jen; Lin, Min-Der

    2013-05-01

    Municipal solid waste management (MSWM) is an important, practical and challenging environmental subject. The processes of a MSWM system include household collection, transportation, treatment, material recycling, compost and disposal. A regional program of MSWM is more complicated owing to the involvement of multi-municipality and multi-facility issues. Therefore, an effective decision support system capable of solving regional MSWM problems is necessary for decision-makers. This article employs linear programming techniques to establish a MSWM decision support system (MSWM-DSS) that is able to determine the least costs of regional MSWM strategies. The results of investigating a real-world case in central Taiwan indicate that a regional program is more economical and efficient. For the redeployment of MSW streams, the relatively least cost of operation for the MSWM system can still be achieved through the re-estimation of the MSWM-DSS. This tool and results are useful for MSWM policy-making in central Taiwan.

  20. Urbanization suitability maps: a dynamic spatial decision support system for sustainable land use

    NASA Astrophysics Data System (ADS)

    Cerreta, M.; De Toro, P.

    2012-11-01

    Recent developments in land consumption assessment identify the need to implement integrated evaluation approaches, with particular attention to the development of multidimensional tools for guiding and managing sustainable land use. Land use policy decisions are implemented mostly through spatial planning and its related zoning. This involves trade-offs between many sectorial interests and conflicting challenges seeking win-win solutions. In order to identify a decision-making process for land use allocation, this paper proposes a methodological approach for developing a Dynamic Spatial Decision Support System (DSDSS), denominated Integrated Spatial Assessment (ISA), supported by Geographical Information Systems (GIS) combined with the Analytic Hierarchy Process (AHP). Through empirical investigation in an operative case study, an integrated evaluation approach implemented in a DSDSS helps produce "urbanization suitability maps" in which spatial analysis combined with multi-criteria evaluation methods proved to be useful for both facing the main issues relating to land consumption as well as minimizing environmental impacts of spatial planning.

  1. Knowledge bases, clinical decision support systems, and rapid learning in oncology.

    PubMed

    Yu, Peter Paul

    2015-03-01

    One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care.

  2. Supporting the personnel reliability decision-making process with artificial intelligence

    SciTech Connect

    Harte, D.C.

    1991-01-01

    Recent legislation concerning personnel security has vastly increased the responsibility and accountability of the security manager. Access authorization, fitness for duty, and personnel security access programs require decisions regarding an individual's trustworthiness and reliability based on the findings of a background investigation. While these guidelines provide significant data and are useful as a tool, limited resources are available to the adjudicator of derogatory information on what is and is not acceptable in terms of granting access to sensitive areas of nuclear plants. The reason why one individual is deemed unacceptable and the next acceptable may be questioned and cause discriminatory accusations. This paper is continuation of discussion on workforce reliability, focusing on the use of artificial intelligence to support the decisions of a security manager. With this support, the benefit of previous decisions helps ensure consistent adjudication of background investigations.

  3. Simulation and modeling efforts to support decision making in healthcare supply chain management.

    PubMed

    AbuKhousa, Eman; Al-Jaroodi, Jameela; Lazarova-Molnar, Sanja; Mohamed, Nader

    2014-01-01

    Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges. PMID:24683333

  4. Data Mashups: Potential Contribution to Decision Support on Climate Change and Health

    PubMed Central

    Fleming, Lora E.; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E.; Depledge, Michael H.; Sarran, Christophe; Osborne, Nicholas J.; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel

    2014-01-01

    Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on “data mashups”. These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers. PMID:24499879

  5. Multi-site evaluation of a clinical decision support system for radiation therapy

    NASA Astrophysics Data System (ADS)

    Deshpande, Ruchi; DeMarco, John; Kessel, Kerstin; Liu, Brent J.

    2016-03-01

    We have developed an imaging informatics based decision support system that learns from retrospective treatment plans to provide recommendations for healthy tissue sparing to prospective incoming patients. This system incorporates a model of best practices from previous cases, specific to tumor anatomy. Ultimately, our hope is to improve clinical workflow efficiency, patient outcomes and to increase clinician confidence in decision-making. The success of such a system depends greatly on the training dataset, which in this case, is the knowledge base that the data-mining algorithm employs. The size and heterogeneity of the database is essential for good performance. Since most institutions employ standard protocols and practices for treatment planning, the diversity of this database can be greatly increased by including data from different institutions. This work presents the results of incorporating cross-country, multi-institutional data into our decision support system for evaluation and testing.

  6. Simulation and Modeling Efforts to Support Decision Making in Healthcare Supply Chain Management

    PubMed Central

    Lazarova-Molnar, Sanja

    2014-01-01

    Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges. PMID:24683333

  7. Development of patient decision support tools for motor neuron disease using stakeholder consultation: a study protocol

    PubMed Central

    Hogden, Anne; Greenfield, David; Caga, Jashelle; Cai, Xiongcai

    2016-01-01

    Introduction Motor neuron disease (MND) is a terminal, progressive, multisystem disorder. Well-timed decisions are key to effective symptom management. To date, there are few published decision support tools, also known as decision aids, to guide patients in making ongoing choices for symptom management and quality of life. This protocol is to develop and validate decision support tools for patients and families to use in conjunction with health professionals in MND multidisciplinary care. The tools will inform patients and families of the benefits and risks of each option, as well as the consequences of accepting or declining treatment. Methods and analysis The study is being conducted from June 2015 to May 2016, using a modified Delphi process. A 2-stage, 7-step process will be used to develop the tools, based on existing literature and stakeholder feedback. The first stage will be to develop the decision support tools, while the second stage will be to validate both the tools and the process used to develop them. Participants will form expert panels, to provide feedback on which the development and validation of the tools will be based. Participants will be drawn from patients with MND, family carers and health professionals, support association workers, peak body representatives, and MND and patient decision-making researchers. Ethics and dissemination Ethical approval for the study has been granted by Macquarie University Human Research Ethics Committee (HREC), approval number 5201500658. Knowledge translation will be conducted via publications, seminar and conference presentations to patients and families, health professionals and researchers. PMID:27053272

  8. GAPS OF DECISION SUPPORT MODELS FOR PIPELINE RENEWAL AND RECOMMENDATIONS FOR IMPROVEMENT (SLIDE)

    EPA Science Inventory

    In terms of the development of software for decision support for pipeline renewal, more attention to date has been paid to the development of asset management models that help an owner decide on which portions of a system to prioritize needed actions. There has been much less wor...

  9. Gaps of Decision Support Models for Pipeline Renewal and Recommendations for Improvement

    EPA Science Inventory

    In terms of the development of software for decision support for pipeline renewal, more attention to date has been paid to the development of asset management models that help an owner decide on which portions of a system to prioritize needed actions. There has been much less w...

  10. Decision Support for Renewal of Wastewater Collection and Water Distribution Systems

    EPA Science Inventory

    The objective of this study was to identify the current decision support methodologies, models and approaches being used for determining how to rehabilitate or replace underground utilities; identify the critical gaps of these current models through comparison with case history d...

  11. Advanced Decision-Support for Coastal Beach Health: Virtual Beach 3.0

    EPA Science Inventory

    Virtual Beach is a free decision-support system designed to help beach managers and researchers construct, evaluate, and operate site-specific statistical models that can predict levels of fecal indicator bacteria (FIB) based on environmental conditions that are more readily mea...

  12. REMOTE SENSING, VISUALIZATION AND DECISION SUPPORT FOR WATERSHED MANAGEMENT AND SUSTAINABLE AGRICULTURE

    EPA Science Inventory

    The integration of satellite and airborne remote sensing, scientific visualization and decision support tools is discussed within the context of management techniques for minimizing the non-point source pollution load of inland waterways and the sustainability of food crop produc...

  13. APPLICATION OF THE US DECISION SUPPORT TOOL FOR MATERIALS AND WASTE MANAGEMENT

    EPA Science Inventory

    EPA¿s National Risk Management Research Laboratory has led the development of a municipal solid waste decision support tool (MSW-DST). The computer software can be used to calculate life-cycle environmental tradeoffs and full costs of different waste management plans or recycling...

  14. DESIGN OF A DECISION SUPPORT SYSTEM FOR SELECTION AND PLACEMENT OF BMPS IN URBAN WATERSHEDS

    EPA Science Inventory

    The U.S. Environmental Protection Agency (USEPA) has funded the development of a decision support system for selection and placement of best management practices (BMPs) at strategic locations in urban watersheds. The primary objective of the system is to provide stormwater manag...

  15. Enhancement of the EPA Stormwater BMP Decision-Support Tool (SUSTAIN)

    EPA Science Inventory

    U.S. Environmental Protection Agency (EPA) has been developing and improving a decision-support tool for placement of stormwater best management practices (BMPs) at strategic locations in urban watersheds. The tool is called the System for Urban Stormwater Treatment and Analysis...

  16. Enhancement of the EPA Stormwater BMP Decision-Support Tool (SUSTAIN) - slides

    EPA Science Inventory

    U.S. Environmental Protection Agency (EPA) has been developing and improving a decision-support tool for placement of stormwater best management practices (BMPs) at strategic locations in urban watersheds. The tool is called the System for Urban Stormwater Treatment and Analysis...

  17. Strengthening Resiliency in Coastal Watersheds: An Ecosystem Services and Ecological Integrity Decision Support System

    EPA Science Inventory

    This product provides an integrated assessment framework linked to a decision support system (DSS) that incorporates the ecological integrity (EI) principles and goals described in detail in the US EPA’s Office of Water’s Healthy Watersheds Program (HWP), with Ecosyst...

  18. Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

    ERIC Educational Resources Information Center

    Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

    2013-01-01

    An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

  19. A web-based intensive care clinical decision support system: from design to evaluation.

    PubMed

    Ozel, Deniz; Bilge, Ugur; Zayim, Nese; Cengiz, Melike

    2013-03-01

    The aim of this study is to develop and evaluate a web-based clinical decision support system (CDSS) containing clinical guidelines and protocols that will support intensive care unit (ICU) providers in making decisions more effectively and quickly. First, a survey was carried out with 38 physicians in order to determine their preferences, needs and concerns regarding decision support tools. After the survey, guidelines were prepared by a group of specialists in ICU, and a medical informatician converted the guidelines into algorithm forms. Ten CDSS were developed using the algorithms, and placed onto the Intensive Care Decision Support Website (ICDSW). In order to evaluation of the website, 15 physicians were asked to answer 10 questions in 10 different scenarios first using a paper-based approach, then with ICDSW. When the answers were analyzed, it was found that the answers given by using ICDSW were significantly better than the paper-based approach (p <  0.001). However, there was no significant difference in terms of the time needed to answer the questions (p =  0.138). The usability score of the website was 85.6 ±  8.89. The study demonstrated the successful implementation of an ICDSW within intensive care units.

  20. Development of a Decision Support System to Predict Physicians' Rehabilitation Protocols for Patients with Knee Osteoarthritis

    ERIC Educational Resources Information Center

    Hawamdeh, Ziad M.; Alshraideh, Mohammad A.; Al-Ajlouni, Jihad M.; Salah, Imad K.; Holm, Margo B.; Otom, Ali H.

    2012-01-01

    To design a medical decision support system (MDSS) that would accurately predict the rehabilitation protocols prescribed by the physicians for patients with knee osteoarthritis (OA) using only their demographic and clinical characteristics. The demographic and clinical variables for 170 patients receiving one of three treatment protocols for knee…

  1. Consensus Recommendations for Systematic Evaluation of Drug-Drug Interaction Evidence for Clinical Decision Support

    PubMed Central

    Scheife, Richard T.; Hines, Lisa E.; Boyce, Richard D.; Chung, Sophie P.; Momper, Jeremiah; Sommer, Christine D.; Abernethy, Darrell R.; Horn, John; Sklar, Stephen J.; Wong, Samantha K.; Jones, Gretchen; Brown, Mary; Grizzle, Amy J.; Comes, Susan; Wilkins, Tricia Lee; Borst, Clarissa; Wittie, Michael A.; Rich, Alissa; Malone, Daniel C.

    2015-01-01

    Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools. PMID:25556085

  2. Decision support for governing boards of integrated delivery networks: explicating versus eliciting knowledge.

    PubMed

    Green, Carolyn J; Moehr, Jochen R

    2003-01-01

    The everyday knowledge work of members of one governing health board was mapped using institutional ethnography. Our objective was to identify opportunities to improve the effective use of information and communication technologies for decision support. The dynamic interplay of work processes, professional discourse, institutional complexes and dominant ideology was explicated, that is, made visible in relation to the actualities of work practices. PMID:14728359

  3. A Data Analytical Framework for Improving Real-Time, Decision Support Systems in Healthcare

    ERIC Educational Resources Information Center

    Yahav, Inbal

    2010-01-01

    In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

  4. OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

  5. Computerizing the Budget Office: An On-Line Decision Support System.

    ERIC Educational Resources Information Center

    Rosenberg, Glenn R.; Peterson, William R.

    The implementation process and resource requirements of the University of Connecticut Budget Office's online decision support system are described. Successes and failures of shifting to a fully interactive budget review and development process are also reviewed. Special attention is given to the personnel problems and analytical challenges…

  6. DEVELOPMENT OF PROTOCOLS AND DECISION SUPPORT TOOLS FOR ASSESSING WATERSHED SYSTEM ASSIMILATIVE

    EPA Science Inventory

    Investigations are underway on Lake Texoma, a Corps of Engineers lake on the Oklahoma/Texas border, to develop decision support tools and information to evaluate the transport and attenuation of contaminants and stressors in a lake ecosystem, and link them to observable ecologica...

  7. 77 FR 29620 - Notice of Availability of Record of Decision for TRIDENT Support Facilities Explosives Handling...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-18

    ... Department of the Navy Notice of Availability of Record of Decision for TRIDENT Support Facilities Explosives Handling Wharf at Naval Base Kitsap at Bangor, Kitsap County, WA AGENCY: Department of the Navy, DoD. ACTION: Notice. SUMMARY: The United States Department of the Navy (DoN), after carefully weighing...

  8. Incorporating exposure information into the toxicological prioritization index decision support framework

    EPA Science Inventory

    The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to po...

  9. End of Asset Life Reinvestment Decision Support Tool (INFR2R11AT)

    EPA Science Inventory

    This “End of Asset Life” Reinvestment Decision-Support Tool is intended as a step by step guide for the asset management practitioner who faces the challenge of developing an investment strategy that represents the best integration of maintenance, operations, and capital investme...

  10. The Integrated Medical Model - A Risk Assessment and Decision Support Tool for Human Space Flight Missions

    NASA Technical Reports Server (NTRS)

    Kerstman, Eric; Minard, Charles G.; Saile, Lynn; FreiredeCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

    2010-01-01

    The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight.

  11. Decision Support Methods for Finding Phenotype — Disorder Associations in the Bone Dysplasia Domain

    PubMed Central

    Paul, Razan; Groza, Tudor; Hunter, Jane; Zankl, Andreas

    2012-01-01

    A lack of mature domain knowledge and well established guidelines makes the medical diagnosis of skeletal dysplasias (a group of rare genetic disorders) a very complex process. Machine learning techniques can facilitate objective interpretation of medical observations for the purposes of decision support. However, building decision support models using such techniques is highly problematic in the context of rare genetic disorders, because it depends on access to mature domain knowledge. This paper describes an approach for developing a decision support model in medical domains that are underpinned by relatively sparse knowledge bases. We propose a solution that combines association rule mining with the Dempster-Shafer theory (DST) to compute probabilistic associations between sets of clinical features and disorders, which can then serve as support for medical decision making (e.g., diagnosis). We show, via experimental results, that our approach is able to provide meaningful outcomes even on small datasets with sparse distributions, in addition to outperforming other Machine Learning techniques and behaving slightly better than an initial diagnosis by a clinician. PMID:23226331

  12. Using Decision Support to Address Racial Disparities in Mental Health Service Utilization

    ERIC Educational Resources Information Center

    Rawal, Purva H.; Anderson, Tanya R.; Romansky, Jill R.; Lyons, John S.

    2008-01-01

    Unfortunately, racial disparities are well documented in the delivery of behavioral health services. This study examines the effects of implementing a decision support process, integrating clinical information into the administration of mental health services, on racial disparities in psychiatric hospital admissions for children in state custody.…

  13. Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

    ERIC Educational Resources Information Center

    Kunisch, Joseph Martin

    2012-01-01

    Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

  14. Computer-Assisted Diagnostic Decision Support: History, Challenges, and Possible Paths Forward

    ERIC Educational Resources Information Center

    Miller, Randolph A.

    2009-01-01

    This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References…

  15. Evaluating the Effectiveness of Nurse-Focused Computerized Clinical Decision Support on Urinary Catheter Practice Guidelines

    ERIC Educational Resources Information Center

    Lang, Robin Lynn Neal

    2012-01-01

    A growing national emphasis has been placed on health information technology (HIT) with robust computerized clinical decision support (CCDS) integration into health care delivery. Catheter-associated urinary tract infection is the most frequent health care-associated infection in the United States and is associated with high cost, high volumes and…

  16. Thinking Processes in Social Workers' Use of a Clinical Decision Support System: A Qualitative Study

    ERIC Educational Resources Information Center

    Monnickendam, Menachem; Savaya, Riki; Waysman, Mark

    2005-01-01

    The authors examined the thinking processes in the use of a decision support system (DSS) by social workers in a human services agency to determine whether they used the system to improve their case reasoning. Information was obtained from in-depth interviews with eight social workers who used a DSS in their work and from content analysis of…

  17. 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…

  18. Decision Support Systems: An Institutional Research Perspective. AIR Forum 1982 Paper.

    ERIC Educational Resources Information Center

    Sheehan, Bernard S.

    Ideas that have been developed in the decision support systems (DSS) literature that seem particularly relevant to institutional research, planning, and analysis (IRPA) are reviewed. In addition, a survey of practitioners in Canadian universities that provides new information on the rapidly changing current state of information technology,…

  19. The Contribution of Decision Support Systems (DSS) to Consolidation of Educational Policies

    ERIC Educational Resources Information Center

    Klein, Joseph; Wasserstein, Mark

    2005-01-01

    Educational policies proposed with and without the aid of Decision Support Systems (DSS) were compared. 120 teachers responded to a questionnaire describing two hypothetical incidents and presenting a series of options with respect to homogeneous and heterogeneous grouping of pupils according to achievement level. After selection of preferred…

  20. Funder Report on Decision Support Systems Project Dissemination Activities, Fiscal Year 1985.

    ERIC Educational Resources Information Center

    Tetlow, William L.

    Dissemination activities for the Decision Support Systems (DSS) for fiscal year (FY) 1985 are reported by the National Center for Higher Education Management Systems (NCHEMS). The main means for disseminating results of the DSS research and development project has been through computer-generated video presentations at meetings of higher education…