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Sample records for rule-based decision support

  1. Connecting the dots: rule-based decision support systems in the modern EMR era.

    PubMed

    Herasevich, Vitaly; Kor, Daryl J; Subramanian, Arun; Pickering, Brian W

    2013-08-01

    The intensive care unit (ICU) environment is rich in both medical device and electronic medical record (EMR) data. The ICU patient population is particularly vulnerable to medical error or delayed medical intervention both of which are associated with excess morbidity, mortality and cost. The development and deployment of smart alarms, computerized decision support systems (DSS) and "sniffers" within ICU clinical information systems has the potential to improve the safety and outcomes of critically ill hospitalized patients. However, the current generations of alerts, run largely through bedside monitors, are far from ideal and rarely support the clinician in the early recognition of complex physiologic syndromes or deviations from expected care pathways. False alerts and alert fatigue remain prevalent. In the coming era of widespread EMR implementation novel medical informatics methods may be adaptable to the development of next generation, rule-based DSS. PMID:23456293

  2. A UMLS-based Knowledge Acquisition Tool for Rule-based Clinical Decision Support System Development

    PubMed Central

    Achour, Soumeya L.; Dojat, Michel; Rieux, Claire; Bierling, Philippe; Lepage, Eric

    2001-01-01

    Decision support systems in the medical field have to be easily modified by medical experts themselves. The authors have designed a knowledge acquisition tool to facilitate the creation and maintenance of a knowledge base by the domain expert and its sharing and reuse by other institutions. The Unified Medical Language System (UMLS) contains the domain entities and constitutes the relations repository from which the expert builds, through a specific browser, the explicit domain ontology. The expert is then guided in creating the knowledge base according to the pre-established domain ontology and condition–action rule templates that are well adapted to several clinical decision-making processes. Corresponding medical logic modules are eventually generated. The application of this knowledge acquisition tool to the construction of a decision support system in blood transfusion demonstrates the value of such a pragmatic methodology for the design of rule-based clinical systems that rely on the highly progressive knowledge embedded in hospital information systems. PMID:11418542

  3. A model-based simulator for testing rule-based decision support systems for mechanical ventilation of ARDS patients.

    PubMed Central

    Sailors, R. M.; East, T. D.

    1994-01-01

    A model-based simulator was developed for testing rule-based decision support systems that manages ventilator therapy of patients with the Adult Respiratory Distress Syndrome (ARDS). The simulator is based on a multi-compartment model of the human body and mathematical models of the gas exchange abnormalities associated with ARDS. Initial testing of this system indicates that model-based simulators are a viable tool for testing rule-based expert systems used in health-care. PMID:7949849

  4. A rule-based clinical decision model to support interpretation of multiple data in health examinations.

    PubMed

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2011-12-01

    Health examinations can obtain relatively complete health information and thus are important for the personal and public health management. For clinicians, one of the most important works in the health examinations is to interpret the health examination results. Continuously interpreting numerous health examination results of healthcare receivers is tedious and error-prone. This paper proposes a clinical decision support system to assist solving above problems. In order to customize the clinical decision support system intuitively and flexibly, this paper also proposes the rule syntax to implement computer-interpretable logic for health examinations. It is our purpose in this paper to describe the methodology of the proposed clinical decision support system. The evaluation was performed by the implementation and execution of decision rules on health examination results and a survey on clinical decision support system users. It reveals the efficiency and user satisfaction of proposed clinical decision support system. Positive impact of clinical data interpretation is also noted. PMID:20703517

  5. A rule-based decision support application for laboratory investigations management.

    PubMed Central

    Boon-Falleur, L.; Sokal, E.; Peters, M.; Ketelslegers, J. M.

    1995-01-01

    The appropriate management of clinical laboratory requests in specialised clinical units often requires the adherence to pre-defined protocols. We evaluated the impact of a rule-based expert system for clinical laboratory investigations management in a pediatric liver transplantation unit of our hospital. After one year, we observed an overall reduction in laboratory resources consumption for transplanted patients (-27%) and a decrease in the percentage of "STAT" requested tests (-44%). The percentage of tests ordered in agreement with the protocols for those patients increased from 33% before the introduction of the expert system to 45% when the system was used. The system was perceived by the clinicians as increasing the overall benefits in use of clinical resources, improving the laboratory data management, and saving time for the execution of laboratory ancillary tasks. PMID:8563292

  6. 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

  7. 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

  8. Rule-based analysis of pilot decisions

    NASA Technical Reports Server (NTRS)

    Lewis, C. M.

    1985-01-01

    The application of the rule identification technique to the analysis of human performance data is proposed. The relation between the language and identifiable consistencies is discussed. The advantages of production system models for the description of complex human behavior are studied. The use of a Monte Carlo significance testing procedure to assure the validity of the rule identification is examined. An example of the rule-based analysis of Palmer's (1983) data is presented.

  9. 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

  10. 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.

  11. Estimating Classification Accuracy for Complex Decision Rules Based on Multiple Scores

    ERIC Educational Resources Information Center

    Douglas, Karen M.; Mislevy, Robert J.

    2010-01-01

    Important decisions about students are made by combining multiple measures using complex decision rules. Although methods for characterizing the accuracy of decisions based on a single measure have been suggested by numerous researchers, such methods are not useful for estimating the accuracy of decisions based on multiple measures. This study…

  12. 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

  13. 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

  14. 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

  15. Tsunami early warning and decision support

    NASA Astrophysics Data System (ADS)

    Steinmetz, T.; Raape, U.; Teßmann, S.; Strobl, C.; Friedemann, M.; Kukofka, T.; Riedlinger, T.; Mikusch, E.; Dech, S.

    2010-09-01

    An innovative newly developed modular and standards based Decision Support System (DSS) is presented which forms part of the German Indonesian Tsunami Early Warning System (GITEWS). The GITEWS project stems from the effort to implement an effective and efficient Tsunami Early Warning and Mitigation System for the coast of Indonesia facing the Sunda Arc along the islands of Sumatra, Java and Bali. The geological setting along an active continental margin which is very close to densely populated areas is a particularly difficult one to cope with, because potential tsunamis' travel times are thus inherently short. National policies require an initial warning to be issued within the first five minutes after an earthquake has occurred. There is an urgent requirement for an end-to-end solution where the decision support takes the entire warning chain into account. The system of choice is based on pre-computed scenario simulations and rule-based decision support which is delivered to the decision maker through a sophisticated graphical user interface (GUI) using information fusion and fast information aggregation to create situational awareness in the shortest time possible. The system also contains risk and vulnerability information which was designed with the far end of the warning chain in mind - it enables the decision maker to base his acceptance (or refusal) of the supported decision also on regionally differentiated risk and vulnerability information (see Strunz et al., 2010). While the system strives to provide a warning as quickly as possible, it is not in its proper responsibility to send and disseminate the warning to the recipients. The DSS only broadcasts its messages to a dissemination system (and possibly any other dissemination system) which is operated under the responsibility of BMKG - the meteorological, climatological and geophysical service of Indonesia - which also hosts the tsunami early warning center. The system is to be seen as one step towards

  16. EcoSys{trademark}: An environmental decision support tool

    SciTech Connect

    Wheelis, W.T.

    1995-12-31

    There is an increasing interest in environmental trade-offs and impacts of competing processes and products over their life cycle. This interest is based on realization that the true environmental burden associated with a product spans all aspects of a product`s life (e.g., extraction of raw materials, manufacturing, use, and disposal). Environmental decisions are complicated due to the many technical, societal, and regulatory perspectives associated with environmental quality. Because of this complexity, there is a need for environmental decision support tools. EcoSys{trademark} is an environmental information and rule based expert system decision support tool being developed at SNL. The goal is to aid designers, process engineers, managers, and others in making environmentally conscious selections of product design and processes. A demonstration of EcoSys will be presented to document the progress being made in the development of such an environmental decision support tool.

  17. 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...

  18. 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.

  19. 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

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

    PubMed

    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

  2. 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.

  3. 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…

  4. STORED GRAIN ADVISOR PRO: DECISION SUPPORT SYSTEM FOR INSECT MANAGEMENT IN COMMERCIAL GRAIN ELEVATORS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A decision support system, Stored Grain Advisor Pro (SGA Pro), was developed to provide insect pest management information for grain stored at commercial elevators. The program uses a model to predict future risk based on current insect density, grain temperature and moisture. A rule-based system wa...

  5. 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.

  6. 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

  7. 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.

  8. GROTTO visualization for decision support

    NASA Astrophysics Data System (ADS)

    Lanzagorta, Marco O.; Kuo, Eddy; Uhlmann, Jeffrey K.

    1998-08-01

    In this paper we describe the GROTTO visualization projects being carried out at the Naval Research Laboratory. GROTTO is a CAVE-like system, that is, a surround-screen, surround- sound, immersive virtual reality device. We have explored the GROTTO visualization in a variety of scientific areas including oceanography, meteorology, chemistry, biochemistry, computational fluid dynamics and space sciences. Research has emphasized the applications of GROTTO visualization for military, land and sea-based command and control. Examples include the visualization of ocean current models for the simulation and stud of mine drifting and, inside our computational steering project, the effects of electro-magnetic radiation on missile defense satellites. We discuss plans to apply this technology to decision support applications involving the deployment of autonomous vehicles into contaminated battlefield environments, fire fighter control and hostage rescue operations.

  9. DECISION-SUPPORT SYSTEM FOR DIAGNOSTICS RESEARCH

    EPA Science Inventory

    In Phase 1 of this research, we will identify existing tools, methods, and models available to support establishment of cause-effect relationships. In Phase 2, we will investigate existing decision support systems and produce an appropriate decision support system design. Based ...

  10. 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

  11. 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

  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. Evaluation of selected environmental decision support software

    SciTech Connect

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

    1997-06-01

    Decision Support Software (DSS) continues to be developed to support analysis of decisions pertaining to environmental management. Decision support systems are computer-based systems that facilitate the use of data, models, and structured decision processes in decision making. The optimal DSS should attempt to integrate, analyze, and present environmental information to remediation project managers in order to select cost-effective cleanup strategies. The optimal system should have a balance between the sophistication needed to address the wide range of complicated sites and site conditions present at DOE facilities, and ease of use (e.g., the system should not require data that is typically unknown and should have robust error checking of problem definition through input, etc.). In the first phase of this study, an extensive review of the literature, the Internet, and discussions with sponsors and developers of DSS led to identification of approximately fifty software packages that met the preceding definition.

  14. 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

  15. 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.

  16. Extraction Of Adverse Events From Clinical Documents To Support Decision Making Using Semantic Preprocessing.

    PubMed

    Gaebel, Jan; Kolter, Till; Arlt, Felix; Denecke, Kerstin

    2015-01-01

    Clinical documentation is usually stored in unstructured format in electronic health records (EHR). Processing the information is inconvenient and time consuming and should be enhanced by computer systems. In this paper, a rule-based method is introduced that identifies adverse events documented in the EHR that occurred during treatment. For this purpose, clinical documents are transformed into a semantic structure from which adverse events are extracted. The method is evaluated in a user study with neurosurgeons. In comparison to a bag of word classification using support vector machines, our approach achieved comparably good results of 65% recall and 78% precision. In conclusion, the rule-based method generates promising results that can support physicians' decision making. Because of the structured format the data can be reused for other purposes as well. PMID:26262330

  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. Grand challenges in clinical decision support.

    PubMed

    Sittig, Dean F; Wright, Adam; Osheroff, Jerome A; Middleton, Blackford; Teich, Jonathan M; Ash, Joan S; Campbell, Emily; Bates, David W

    2008-04-01

    There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: improve the human-computer interface; disseminate best practices in CDS design, development, and implementation; summarize patient-level information; prioritize and filter recommendations to the user; create an architecture for sharing executable CDS modules and services; combine recommendations for patients with co-morbidities; prioritize CDS content development and implementation; create internet-accessible clinical decision support repositories; use freetext information to drive clinical decision support; mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare. PMID:18029232

  19. 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.

  20. A qualitative study of clinicians ways of using a decision-support system.

    PubMed Central

    Karlsson, D.; Ekdahl, C.; Wigertz, O.; Forsum, U.

    1997-01-01

    We have studied how clinicians approached a decision-support system to manage patient cases. The design of the system under study was based on an integration of hypertext and rule-based systems. World-Wide Web technology was used for the implementation of the system. By using grounded theory and stimulated recall, we found that getting patient-specific support and continuing medical education were the two major usages of the system and that the three parameters relevance, validity, and work were important in describing how the system was experienced by the users. PMID:9357630

  1. 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

  2. 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

  3. Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

    PubMed

    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

  4. 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

  5. Use of conditional rule structure to automate clinical decision support: a comparison of artificial intelligence and deterministic programming techniques.

    PubMed

    Friedman, R H; Frank, A D

    1983-08-01

    A rule-based computer system was developed to perform clinical decision-making support within a medical information system, oncology practice, and clinical research. This rule-based system, which has been programmed using deterministic rules, possesses features of generalizability, modularity of structure, convenience in rule acquisition, explanability, and utility for patient care and teaching, features which have been identified as advantages of artificial intelligence (AI) rule-based systems. Formal rules are primarily represented as conditional statements; common conditions and actions are stored in system dictionaries so that they can be recalled at any time to form new decision rules. Important similarities and differences exist in the structure of this system and clinical computer systems utilizing artificial intelligence (AI) production rule techniques. The non-AI rule-based system possesses advantages in cost and ease of implementation. The degree to which significant medical decision problems can be solved by this technique remains uncertain as does whether the more complex AI methodologies will be required. PMID:6352165

  6. 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.

  7. 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.

  8. A Multiple Objective Decision Support Tool (MODS)

    Energy Science and Technology Software Center (ESTSC)

    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. Response-time optimization of rule-based expert systems

    NASA Astrophysics Data System (ADS)

    Zupan, Blaz; Cheng, Albert M. K.

    1994-03-01

    Real-time rule-based decision systems are embedded AI systems and must make critical decisions within stringent timing constraints. In the case where the response time of the rule- based system is not acceptable, it has to be optimized to meet both timing and integrity constraints. This paper describes a novel approach to reduce the response time of rule-based expert systems. Our optimization method is twofold: the first phase constructs the reduced cycle-free finite state transition system corresponding to the input rule-based system, and the second phase further refines the constructed transition system using the simulated annealing approach. The method makes use of rule-base system decomposition, concurrency, and state- equivalency. The new and optimized system is synthesized from the derived transition system. Compared with the original system, the synthesized system has fewer number of rule firings to reach the fixed point, is inherently stable, and has no redundant rules.

  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. PMID:25748599

  11. Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS

    NASA Astrophysics Data System (ADS)

    Tehrany, Mahyat Shafapour; Pradhan, Biswajeet; Jebur, Mustafa Neamah

    2013-11-01

    Decision tree (DT) machine learning algorithm was used to map the flood susceptible areas in Kelantan, Malaysia.We used an ensemble frequency ratio (FR) and logistic regression (LR) model in order to overcome weak points of the LR.Combined method of FR and LR was used to map the susceptible areas in Kelantan, Malaysia.Results of both methods were compared and their efficiency was assessed.Most influencing conditioning factors on flooding were recognized.

  12. Clinical Decision Support Systems for Ambulatory Care

    PubMed Central

    Lloyd, Stephen C.

    1984-01-01

    This conference serves to further the state of the art in the application of computers to medical care via a forum for the intercommunication of ideas. Papers discuss the experiences of diverse research projects. It is the purpose of this article to review the major developments in ambulatory care decision support. From this vantage point, the major impediments to broad applicability of information systems are discussed. The DUCHESS Medical Information Management System is then described as a step towards overcoming these obstacles. Two distinct but often overlapping issues are the representation of the data and its subsequent manipulation: records vs. knowledge. The complexity of the medical record requires state-of-the-art computer science. Clinical decision support requires flexible means for representing medical knowledge and the ability to input “rules.” Artificial intelligence has provided tools for simulating the decision making processes. A sample of the major systems are contrasted and compared. In the realm of medical records COSTAR, TMR, SCAMP, HELP, and STOR are considered. In clinical decision support CADEUCUS, REGENSTRIEF, PKC, and DUCHESS are reviewed.

  13. 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.

  14. Interactive decision support in hepatic surgery

    PubMed Central

    Dugas, Martin; Schauer, Rolf; Volk, Andreas; Rau, Horst

    2002-01-01

    Background Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques. Methods To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient. Results The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996–2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases. Conclusion Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback. PMID:12003639

  15. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Hawkins, L.; He, M.; Ebersole, S.

    2010-12-01

    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 SANDS project is also investigating the effects of sediment immersed oil from the Deepwater Horizon disaster in April 2010 which has the potential to resurface as a result of tropical storm activity. 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 Sediment Analysis Network for Decision Support has generated a number of decision support products derived from MODIS, Landsat and SeaWiFS instruments that potentially support

  16. Modelling and Decision Support of Clinical Pathways

    NASA Astrophysics Data System (ADS)

    Gabriel, Roland; Lux, Thomas

    The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

  17. Decision support in an imperfect world

    SciTech Connect

    Chang, C.L.

    1983-01-01

    By a decision support system it is meant an expert system that the user can use to inquire about information to make his decision. Such a system will be based on an expert knowledge base. It is believed that the knowledge base is more than facts and rules. It may include less tangible and less codifiable factors like opinions, judgments, educated guesses, as well as factual information and logic rules for reasoning. That is, the knowledge may be explicit, logical, heuristic, or fuzzy. This paper presents some methods to add fuzzy information into a relational data base. Specifically it considers the treatments of fuzzy queries. An answer to a fuzzy query will be a fuzzy set from which a further detailed study can be made. 13 references.

  18. 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.

  19. 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.

  20. Linquistic geometry: new technology for decision support

    NASA Astrophysics Data System (ADS)

    Stilman, Boris; Yakhnis, Vladimir

    2003-09-01

    Linguistic Geometry (LG) is a revolutionary gaming approach which is ideally suited for military decision aids for Air, Ground, Naval, and Space-based operations, as well guiding robotic vehicles and traditional entertainment games. When thinking about modern or future military operations, the game metaphor comes to mind right away. Indeed, the air space together with the ground and seas may be viewed as a gigantic three-dimensional game board. Refining this picture, the LG approach is capable of providing an LG hypergame, that is, a system of multiple concurrent interconnected multi-player abstract board games (ABG) of various resolutions and time frames reflecting various kinds of hardware and effects involved in the battlespace and the solution space. By providing a hypergame representation of the battlespace, LG already provides a significant advance in situational awareness. However, the greatest advantage of the LG approach is an ability to provide commanders of campaigns and missions with decision options resulting in attainment of the commander's intent. At each game turn, an LG decision support tool assigns the best actions to each of the multitude of battlespace actors (UAVs, bombers, cruise missiles, etc.). This is done through utilization of algorithms finding winning strategies and tactics, which are the core of the LG approach.

  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. Decision support software technology demonstration plan

    SciTech Connect

    SULLIVAN,T.; ARMSTRONG,A.

    1998-09-01

    The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.

  4. 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

  5. Special Issue: Decision Support and Knowledge-Based Systems.

    ERIC Educational Resources Information Center

    Stohr, Edward A.; And Others

    1987-01-01

    Six papers dealing with decision support and knowledge based systems are presented. Five of the papers are concerned in some way with the use of artificial intelligence techniques in individual or group decision support. The sixth paper presents empirical results from the use of a group decision support system. (CLB)

  6. 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

  7. 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

  8. 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...

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

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 12 Banks and Banking 9 2013-01-01 2013-01-01 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. 12 CFR 1290.4 - Decision on community support statements.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 12 Banks and Banking 10 2014-01-01 2014-01-01 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...

  11. 12 CFR 1290.4 - Decision on community support statements.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 12 Banks and Banking 9 2012-01-01 2012-01-01 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...

  12. Decision Support Systems in Diuresis Renography

    PubMed Central

    Taylor, Andrew; Manatunga, Amita; Garcia, Ernest V.

    2013-01-01

    The volume of diagnostic imaging studies performed in the United States is rapidly increasing resulting from an increase in the number of patients as well as an increase in the volume of studies per patient. Concurrently, the number and complexity of images in each patient data set are also increasing. Nuclear medicine physicians and radiologists are required to master an ever-expanding knowledge base whereas the hours available to master this knowledge base and apply it to specific tasks are steadily shrinking. The convergence of an expanding knowledge base and escalating time constraints increases the likelihood of physician errors. The problem is particularly acute for low-volume studies such as MAG3 diuresis renography where many imagers may have had limited training or experience. To address this problem, renal decision support systems (DSS) are being developed to assist physicians evaluate suspected obstruction in patients referred for diuresis renography. Categories of DSS include neural networks, case-based reasoning, expert systems and statistical systems; RENEX and CART are examples of renal DSS currently in development. RENEX (renal expert) uses a set of rules obtained from human experts to analyze a knowledge base of expanded quantitative parameters obtained from diuresis MAG3 scintigraphy whereas CART (classification and regression tree analysis) is a statistical method that grows and prunes a decision tree based on an analysis of these quantitative parameters in a training data set. RENEX can be queried to provide the reasons for its conclusions. Initial data show that the interpretations provided by RENEX and CART are comparable to the interpretations of a panel of experts blinded to clinical information. This project should serve as a benchmark for the scientific comparison and collaboration of these 2 fields of medical decision-making. Moreover, we anticipate that these DSS will better define the essential interpretative criteria, foster

  13. Decision investigation and support environment (DISE)

    NASA Astrophysics Data System (ADS)

    VonPlinsky, Michael J.; Johnson, Pete; Crowder, Ed

    2001-09-01

    The "Decision Integration and Support Environment" (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision process. FTI has developed two BNs to model these processes, incorporating aircraft, target, and overall mission priorities from the Air Operations Center (OAC) and the mission planners/command staff. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR Sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosectued, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process, including factors such as: * Fuel Level - amount of fuel in aircraft * Type of Weapon - available weapons on board aircraft * Probability of Survival - depends on the type of TST, time criticality and other factors * Potential Collateral Damage - amount of damage incurred on TST surroundings * Time Criticality of TST - how "critical" it is to attack the target depending on its launch status * Time to Target - aircraft's distance (in minutes) from the TST * Current Mission Priority - priority of the mission to which the aircraft is currently assigned * TST Mission Priority - determined when the target is originally nominated * Possible Reassignment - represents whether it is even possible to reassign the aircraft * Aircraft Re-tasking Availability - represents any factor not taken into account by the model, including commander override.

  14. Decision Support for Active Water Management (Invited)

    NASA Astrophysics Data System (ADS)

    Maidment, D. R.; Salas, F.; Minsker, B. S.

    2013-12-01

    Active water management refers to real-time adjustment of water management decisions based on observation and modeling of current water conditions. A case study is presented of a decision-support system for active water management in the San Antonio and Guadalupe basins using web services and cloud computing to create at the University of Texas a repository of observations, forecasts and model simulations from federal, state and regional water agencies and academia. Each day, National Weather Service river flow forecasts at 47 points in the basin are densified to create corresponding flows in 5500 river reaches using the RAPID river flow model operated in "Model as a Service" mode at the University of Illinois. These flows are adjusted by using the "Declarations of Intent" to pump water compiled by the Texas Commission for Environmental Quality which is the WaterMaster for all surface water withdrawals in the basin. The results are viewed through web maps that convey both maps of the spatial pattern of flow at a particular point in time, and charts of time series of flows at particular points in space.

  15. 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

  16. 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).

  17. Clinical evaluation of the DIABETES expert system for decision support by multiple regimen insulin dose adjustment.

    PubMed

    Ambrosiadou, B V; Goulis, D G; Pappas, C

    1996-01-01

    A performance evaluation of the DIABETES rule-based expert system prototype for clinical decision making is presented. The system facilitates multiple insulin regimen and dose adjustment of insulin dependent Type I or II diabetic patients. The study was performed on 600 subjects from two diabetological centres and three diabetological offices of Greek hospitals. The responses of the attendant medical doctors were compared with those of the DIABETES system, with the aid of a specifically devised valuation range (0-5 degrees, 0 indicating full agreement and 5 full disagreement). The capabilities and the weakness of the system in terms of its practicality for decision support in assisting therapy of diabetes mellitus by blood glucose monitoring and subsequent insulin dose adjustment are discussed. The potential benefits of decision support systems for diabetic patient management are seen to be the cost saving they provide in terms of man-hours of verbal instruction by medical experts, the support in terms of objective and consistent decision making, as well as the recording of medical knowledge in the ill-defined field of insulin administration, thus aiding the education and training of medical personnel. PMID:8646833

  18. Novel Architecture for supporting medical decision making of different data types based on Fuzzy Cognitive Map Framework.

    PubMed

    Papageorgiou, Elpiniki; Stylios, Chrysostomos; Groumpos, Peter

    2007-01-01

    Medical problems involve different types of variables and data, which have to be processed, analyzed and synthesized in order to reach a decision and/or conclude to a diagnosis. Usually, information and data set are both symbolic and numeric but most of the well-known data analysis methods deal with only one kind of data. Even when fuzzy approaches are considered, which are not depended on the scales of variables, usually only numeric data is considered. The medical decision support methods usually are accessed in only one type of available data. Thus, sophisticated methods have been proposed such as integrated hybrid learning approaches to process symbolic and numeric data for the decision support tasks. Fuzzy Cognitive Maps (FCM) is an efficient modelling method, which is based on human knowledge and experience and it can handle with uncertainty and it is constructed by extracted knowledge in the form of fuzzy rules. The FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This rule base could be derived by a number of machine learning and knowledge extraction methods. Here it is introduced a hybrid attempt to handle situations with different types of available medical and/or clinical data and with difficulty to handle them for decision support tasks using soft computing techniques. PMID:18002176

  19. 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

  20. 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

  1. 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.

  2. Architecting next 30 years of climate monitoring from space with instructive examples from NPOESS and GCOS plus new rule-based decision tools: suggesting and promoting global collaborative paths forward (Part V)

    NASA Astrophysics Data System (ADS)

    Helmuth, Douglas B.; Bell, Raymond M.; Lentz, Christopher A.

    2013-10-01

    Collecting the earth's critical climate signatures over the next 30 years is an obvious priority for many world governments and international organizations. Implementing a solution requires bridging from today's scientific missions to `operational' constellations that are adequate to support the future demands of decision makers, scientific investigators and global users for trusted data.

  3. What is the next step in patient decision support?

    PubMed Central

    Scott, G. C.; Lenert, L. A.

    2000-01-01

    Patient decision support systems have a promising role in the delivery of health care. However, the best approach for further development of these systems is a matter of speculation. To help chart a course for further development of decision support systems, we consider the four traditional roles that patients play in the medical decision making process, the limitations that patients face in participating in each role and describe how contemporary systems address can facilitate successful decision making for each role. Because patients have a diversity of preferences for the role they play in decision making, we believe that the critical research question is how to make decision support systems robust enough to support a patient's desired role, whatever that role might be. By directing research in decision support systems in this fashion, we believe that they will achieve a larger patient audience and have increased value in the delivery of clinical care. PMID:11079991

  4. Decision support using causation knowledge base

    SciTech Connect

    Nakamura, K.; Iwai, S.; Sawaragi, T.

    1982-11-01

    A decision support system using a knowledge base of documentary data is presented. Causal assertions in documents are extracted and organized into cognitive maps, which are networks of causal relations, by the methodology of documentary coding. The knowledge base is constructed by joining cognitive maps of several documents concerned with a societal complex problem. The knowledge base is an integration of several expertises described in documents, though it is only concerned with causal structure of the problem, and includes overall and detailed information about the problem. Decisionmakers concerned with the problem interactively retrieve relevant information from the knowledge base in the process of decisionmaking and form their overall and detailed understanding of the complex problem based on the expertises stored in the knowledge base. Three retrieval modes are proposed according to types of the decisionmakers requests: 1) skeleton maps indicate overall causal structure of the problem, 2) hierarchical graphs give detailed information about parts of the causal structure, and 3) sources of causal relations are presented when necessary, for example when the decisionmaker wants to browse the causal assertions in documents. 10 references.

  5. Supporting patients in shared decision making in clinical practice.

    PubMed

    Madsen, Claire; Fraser, Aileen

    2015-04-01

    This article defines shared decision making in patient care and describes the background to this philosophy. The shared decision making approach is part of a wider initiative to promote patient-centred care and increase patient involvement in clinical decisions. Shared decision making recognises patients' rights to make decisions about their care and is used to assist them to make informed and individualised decisions about care and treatment. As well as reviewing the principles of shared decision making, the article offers practical guidance on how nurses can implement this initiative, including information on sharing expertise, agenda setting, assessing risks and benefits, setting goals, and support and follow up. PMID:25828022

  6. 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...

  7. A Framework and Model for Evaluating Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper, we develop a four-phase model for evaluating architectures for clinical decision support that focuses on: defining a set of desirable features for a decision support architecture; building a proof-of-concept prototype; demonstrating that the architecture is useful by showing that it can be integrated with existing decision support systems and comparing its coverage to that of other architectures. We apply this framework to several well-known decision support architectures, including Arden Syntax, GLIF, SEBASTIAN and SAGE PMID:18462999

  8. 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...

  9. Decision support in an integrated environment

    NASA Astrophysics Data System (ADS)

    Collie, Brad E.; Wallace, Daniel F.; Humphrey, Andy W.

    2000-11-01

    As the United States Navy enters into an era of reduced manning, the role of the decision maker and that of automation must change in order to maintain an acceptable level of performance. In the past, the responsibility of information synthesis has typically fallen on the operator. This becomes problematic when there is a lack of systems integration (most often technologies are co-located but not integrated), thus causing the operator to process an undue amount of information when analyzing information across multiple systems. Reducing the number of operators without changing the way decisions are made would result in information overload, delayed/degraded decision-making, and increased errors/accidents. If we are to successfully take sailors off ships, we must consider decision making in a new manner. One way to address the situation is to provide the decision maker/operator with a Knowledge Management System (KMS), which reduces cognitive processing requirements on behalf of the operator. For example, decisions based on doctrine can be automated with little impact on the quality of the decision as long as the operator is informed of what actions have been taken (keeping the operator in the loop). This paper will address the definition of Knowledge, the need for a KMS, functional allocation of Knowledge processing, and how systems can be designed for Knowledge Management concepts.

  10. 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.

  11. On Two Roles Decision Support Systems Can Play in Negotiations.

    ERIC Educational Resources Information Center

    Kersten, Gregory E.

    1987-01-01

    Focuses on the role of the computer system in group decision making. Two systems used in solving negotiating problems--NEGO and MEDIATOR--and three procedures that can be utilized to develop group decision support systems are analyzed, based on multicriteria decision analysis and mathematical programming models. (Author/LRW)

  12. 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...

  13. Improvement of sand filter and constructed wetland design using an environmental decision support system.

    PubMed

    Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

    2008-01-01

    With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal. PMID:18574198

  14. Outpatient diabetes clinical decision support: current status and future directions.

    PubMed

    O'Connor, P J; Sperl-Hillen, J M; Fazio, C J; Averbeck, B M; Rank, B H; Margolis, K L

    2016-06-01

    Outpatient clinical decision support systems have had an inconsistent impact on key aspects of diabetes care. A principal barrier to success has been low use rates in many settings. Here, we identify key aspects of clinical decision support system design, content and implementation that are related to sustained high use rates and positive impacts on glucose, blood pressure and lipid management. Current diabetes clinical decision support systems may be improved by prioritizing care recommendations, improving communication of treatment-relevant information to patients, using such systems for care coordination and case management and integrating patient-reported information and data from remote devices into clinical decision algorithms and interfaces. PMID:27194173

  15. 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.

  16. 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.

  17. 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…

  18. Automated rule-base creation via CLIPS-Induce

    NASA Technical Reports Server (NTRS)

    Murphy, Patrick M.

    1994-01-01

    Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.

  19. 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…

  20. 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...

  1. 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…

  2. Information visualization in a distributed virtual decision support environment

    NASA Astrophysics Data System (ADS)

    Blocher, Timothy W.

    2002-07-01

    The visualization of and interaction with decision quality information is critical for effective decision makers in today's data rich environments. The generation and presentation of intuitively meaningful decision support information is the challenge. In order to investigate various visualization approaches to improve the timeliness and quality of Commander decisions, a robust, distributed virtual simulation environment, based on AFRL's Global Awareness Virtual Testbed (GAVTB), is being developed to represent an Air Operations Center (AOC) environment. The powerful Jview visualization technology is employed to efficiently and effectively utilize the simulation products to experiment with various decision quality representations and interactions required by military commanders.

  3. Decision support for redesigning wastewater treatment technologies.

    PubMed

    McConville, Jennifer R; Künzle, Rahel; Messmer, Ulrike; Udert, Kai M; Larsen, Tove A

    2014-10-21

    This paper offers a methodology for structuring the design space for innovative process engineering technology development. The methodology is exemplified in the evaluation of a wide variety of treatment technologies for source-separated domestic wastewater within the scope of the Reinvent the Toilet Challenge. It offers a methodology for narrowing down the decision-making field based on a strict interpretation of treatment objectives for undiluted urine and dry feces and macroenvironmental factors (STEEPLED analysis) which influence decision criteria. Such an evaluation identifies promising paths for technology development such as focusing on space-saving processes or the need for more innovation in low-cost, energy-efficient urine treatment methods. Critical macroenvironmental factors, such as housing density, transportation infrastructure, and climate conditions were found to affect technology decisions regarding reactor volume, weight of outputs, energy consumption, atmospheric emissions, investment cost, and net revenue. The analysis also identified a number of qualitative factors that should be carefully weighed when pursuing technology development; such as availability of O&M resources, health and safety goals, and other ethical issues. Use of this methodology allows for coevolution of innovative technology within context constraints; however, for full-scale technology choices in the field, only very mature technologies can be evaluated. PMID:25225855

  4. Provider perspectives on electronic decision supports for obesity prevention.

    PubMed

    Dryden, Eileen M; Hardin, Jessica; McDonald, Julia; Taveras, Elsie M; Hacker, Karen

    2012-05-01

    Despite the availability of national evidenced-based guidelines related to pediatric obesity screening and prevention, multiple studies have shown that primary care physicians find it difficult to adhere to them or are unfamiliar with them altogether. This article presents physicians' perspectives on the use of electronic decision support tools, an alert and Smart Set, to accelerate the adoption of obesity-related recommendations into their practice. The authors interviewed providers using a test encounter walk-through technique that revealed a number of barriers to using electronic decision supports for obesity care in primary care settings. Providers' suggestions for improving their use of obesity-related decision supports are presented. Careful consideration must be given to both the development of electronic decision support tools and a multilayered educational outreach strategy if providers are going to be persuaded to use such supports to help them implement pediatric obesity prevention and management best practices. PMID:22330047

  5. 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.

  6. 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.

  7. A decision support system for automatic screening of non-proliferative diabetic retinopathy.

    PubMed

    Reza, Ahmed Wasif; Eswaran, C

    2011-02-01

    The increasing number of diabetic retinopathy (DR) cases world wide demands the development of an automated decision support system for quick and cost-effective screening of DR. We present an automatic screening system for detecting the early stage of DR, which is known as non-proliferative diabetic retinopathy (NPDR). The proposed system involves processing of fundus images for extraction of abnormal signs, such as hard exudates, cotton wool spots, and large plaque of hard exudates. A rule based classifier is used for classifying the DR into two classes, namely, normal and abnormal. The abnormal NPDR is further classified into three levels, namely, mild, moderate, and severe. To evaluate the performance of the proposed decision support framework, the algorithms have been tested on the images of STARE database. The results obtained from this study show that the proposed system can detect the bright lesions with an average accuracy of about 97%. The study further shows promising results in classifying the bright lesions correctly according to NPDR severity levels. PMID:20703589

  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 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)

  10. 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...

  11. 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...

  12. Integrated Modelling Frameworks for Environmental Assessment and Decision Support

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Modern management of environmental resources defines problems from a holistic and integrated perspective, imposing strong requirements to Environmental Decision Support Systems (EDSSs) and Integrated Assessment Tools (IATs), which tend to be increasingly complex in terms of software architecture and...

  13. 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'…

  14. Discern--an integrated prospective decision support system.

    PubMed Central

    Johnson, B.; McNair, D.; Kailasam, K.; Reilly, R.; Eklund, N.; McCoy, G.; Jamieson, P.

    1994-01-01

    We present a new integrated decision support tool, called Discern, for prospective case management within a comprehensive Healthcare Network Architecture (HNA). Discern is an event-driven, expert system tightly integrated into this architecture. It can perform a variety of actions including generating alerts, ordering tests, and entering results. Over 100 institutions use Discern to automate care processes. Discern was designed to meet the demanding requirements for effective decision support. PMID:7950073

  15. 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

  16. 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

  17. Supporting contractors' bidding decision: RBF neural networks application

    NASA Astrophysics Data System (ADS)

    Leśniak, Agnieszka

    2016-06-01

    A bidding decision, despite its being important for the contractor, often needs to be made quickly and within a limited timeframe. To facilitate the contractor's reasoning by limiting randomness that may lead to mistakes decision support models are frequently applied. This paper presents possible applications of an Artificial Neural Network (ANN) to support bidding decisions. The proposed model involving networks with radial basis functions (RBF) was to perform a classification task. On the basis of a set of input data, the network was to suggest either participation in the bid or resignation from it. The results, 93% of correctly classified cases, confirmed the usability of RBF network in solving the problem.

  18. Prolog: A Practical Language for Decision Support Systems in Nursing?

    PubMed Central

    Ozbolt, Judy G.

    1987-01-01

    Developing decision support systems for nursing has been limited by difficulties in defining and representing nursing's knowledge base and by a lack of knowledge of how nurses make decisions. Recent theoretical and empirical work offers solutions to those problems. The challenge now is to represent nursing knowledge in a way that is comprehensible to both nurse and computer and to design decision support modalities that are accurate, efficient, and appropriate for nurses with different levels of expertise. This paper reviews the issues and critically evaluates Prolog as a tool for meeting the challenge.

  19. 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.

  20. OPENING COMMENTS TO THE SPECIAL SESSION ON DECISION SUPPORT TOOLS.

    SciTech Connect

    SULLIVAN,T.; BARDOS,P.

    2000-06-01

    The emphasis of the session was on the use of decision support tools for actual remediation decisions. It considered two perspectives: site-specific decision making for example choosing a particular remediation system; and remediation in terms of a risk management/risk reduction process as part of a wider process of site management. These were addressed both as general topics and as case studies. Case studies were included to provide information on decision support techniques for specific contamination problems such as remedy selection. In the case studies, the authors present the general process to provide decision support and then discuss the application to a specific problem. The intent of this approach is to provide the interested reader with enough knowledge to determine if the process could be used on their specific set of problems. The general topics included broader issues that are not directly tied to a specific problem. The general topics included papers on the role of stakeholders in the decision process and decision support approaches for sustainable development.

  1. System-agnostic clinical decision support services: benefits and challenges for scalable decision support.

    PubMed

    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

  2. Evaluating Detection and Diagnostic Decision Support Systems for Bioterrorism Response

    PubMed Central

    Sundaram, Vandana; McDonald, Kathryn M.; Smith, Wendy M.; Szeto, Herbert; Schleinitz, Mark D.; Owens, Douglas K.

    2004-01-01

    We evaluated the usefulness of detection systems and diagnostic decision support systems for bioterrorism response. We performed a systematic review by searching relevant databases (e.g., MEDLINE) and Web sites for reports of detection systems and diagnostic decision support systems that could be used during bioterrorism responses. We reviewed over 24,000 citations and identified 55 detection systems and 23 diagnostic decision support systems. Only 35 systems have been evaluated: 4 reported both sensitivity and specificity, 13 were compared to a reference standard, and 31 were evaluated for their timeliness. Most evaluations of detection systems and some evaluations of diagnostic systems for bioterrorism responses are critically deficient. Because false-positive and false-negative rates are unknown for most systems, decision making on the basis of these systems is seriously compromised. We describe a framework for the design of future evaluations of such systems. PMID:15078604

  3. 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.

  4. 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

  5. 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...

  6. 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…

  7. 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…

  8. 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.

  9. Risk Analysis Based Business Rule Enforcement for Intelligent Decision Support

    NASA Astrophysics Data System (ADS)

    Vasilecas, Olegas; Smaizys, Aidas; Brazinskas, Ramunas

    Intelligent information systems are acting by structured rules and do not deal with possible impact on the business environment or future consequences. That is the main reason why automated decisions based on such rules cannot take responsibility and requires involvement or approval of dedicated business people. This limits decision automation possibilities in information systems. However, business rules describe business policy and represent business logics. This can be used in intelligent information systems, together with risk assessment model to simulate real business environment and evaluate possible impact of automated decisions, to support intelligent decision automation. The chapter proposes risk and business rule model integration to provide full intelligent decision automation model used for business rule enforcement and implementation into intelligent software systems of information systems.

  10. 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

  11. Improving clinical decision support using data mining techniques

    NASA Astrophysics Data System (ADS)

    Burn-Thornton, Kath E.; Thorpe, Simon I.

    1999-02-01

    Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.

  12. 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

  13. 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. PMID:25927513

  14. 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. PMID:25571435

  15. 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.

  16. 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

  17. System for selecting relevant information for decision support.

    PubMed

    Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana

    2013-01-01

    We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data. PMID:23542973

  18. Hybrid methods for multisource information fusion and decision support

    NASA Astrophysics Data System (ADS)

    Braun, Jerome J.; Glina, Yan

    2006-04-01

    This paper presents the progress of an ongoing research effort in multisource information fusion for biodefense decision support. The effort concentrates on a novel machine-intelligence hybrid-of-hybrids decision support architecture termed FLASH (Fusion, Learning, Adaptive Super-Hybrid) we proposed. The highlights of FLASH discussed in the paper include its cognitive-processing orientation and the hybrid nature involving heterogeneous multiclassifier machine learning and approximate reasoning paradigms. Selected specifics of the FLASH internals, such as its feature selection techniques, supervised learning, clustering, recognition and reasoning methods, and their integration, are discussed. The results to date are presented, including the background type determination and bioattack detection computational experiments using data obtained with a multisensor fusion testbed we have also developed. The processing of imprecise information originating from sources other than sensors is considered. Finally, the paper discusses applicability of FLASH and its methods to complex battlespace management problems such as course-of-action decision support.

  19. 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.

  20. 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

  1. 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. PMID:24491614

  2. 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.

  3. An intelligent fuzzy decision support system for production management

    SciTech Connect

    Vojdani, N.

    1996-11-01

    In the near future the optimizing of production processes in terms of reducing order lead times, delivery times, inventory stocks and production costs, while increasing the flexibility, productivity and quality of all operations will become a matter of survival for many manufacturing enterprises. This paper presents an application using an intelligent fuzzy decision support system in production management. It is based on a goal oriented logistics index numbers system and ensures the competitive capacity of manufacturing enterprises by indicating the means to achieve management goals. The aim is to demonstrate the main properties of the fuzzy decision support system PROMAN.

  4. Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems

    PubMed Central

    Sarwar, Mansoor

    2014-01-01

    Many problems of practical interest can be modeled and solved by using graph algorithms. In general, graph theory has a wide range of applications in diverse fields. In this paper, the intuitionistic fuzzy organizational and neural network models, intuitionistic fuzzy neurons in medical diagnosis, intuitionistic fuzzy digraphs in vulnerability assessment of gas pipeline networks, and intuitionistic fuzzy digraphs in travel time are presented as examples of intuitionistic fuzzy digraphs in decision support system. We have also designed and implemented the algorithms for these decision support systems. PMID:25045752

  5. 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

  6. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: PUBLISHED REPORT

    EPA Science Inventory

    NRMRL-CIN-1351A Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. EPA/600/R-01/104 (NTIS PB2002-102119). Decision makers using environmental decision support tools are often ...

  7. Using hierarchically structured problem-solving knowledge in a rule-based process planning system

    SciTech Connect

    Hummel, K.E.; Brooks, S.L.

    1987-06-01

    A rule-based expert system, XCUT, currently is being developed which will generate process plans for the production of machined parts, given a feature-based part description. Due to the vast and dynamic nature of process planning knowledge, a technique has been used in the development of XCUT that segments problem solving knowledge into multiple rule bases. These rule bases are structured in a hierarchical manner that is reflective of the problem decomposition procedure used to generate a plan. An inference engine, HERB (Hierarchical Expert Rule Bases), has been developed which supports the manipulation of multiple rule bases during the planning process. This paper illustrates the hierarchical nature of problem-solving knowledge in the XCUT system and describes the use of HERB for programming with hierarchically structured rule bases. 6 refs., 21 figs.

  8. 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.

  9. An object-oriented approach to site characterization decision support

    SciTech Connect

    Johnson, R.

    1995-06-01

    Effective decision support for site characterization is key to determining the nature and extent of contamination and the associated human and environmental risks. Site characterization data, however, present particular problems to technical analysts and decision-makers. Such data are four dimensional, incorporating temporal and spatial components. Their sheer volume can be daunting -- sites with hundreds of monitoring wells and thousands of samples sent for laboratory analyses are not uncommon. Data are derived from a variety of sources including laboratory analyses, non-intrusive geophysical surveys, historical information, bore logs, in-field estimates of key physical parameters such as aquifer transmissivity, soil moisture content, depth-to-water table, etc. Ultimately, decisions have to be made based on data that are always incomplete, often confusing, inaccurate, or inappropriate, and occasionally wrong. In response to this challenge, two approaches to environmental decision support have arisen, Data Quality Objectives (DQOS) and the Observational Approach (OA). DQOs establish criteria for data collection by clearly defining the decisions that need to be made, the uncertainty that can be tolerated, and the type and amount of data that needs to be collected to satisfy the uncertainty requirements. In practice, DQOs are typically based on statistical measures. The OA accepts the fact that the process of characterizing and remediating contaminated sites is always uncertain. Decision-making with the OA is based on what is known about a site, with contingencies developed for potential future deviations from the original assumptions about contamination nature, extent, and risks posed.

  10. Decision analysis as a life support technology assessment capability.

    PubMed

    Ballin, M G

    1995-01-01

    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, especially in a resource-constrained environment. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by 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 confronting a decision maker. It also accounts for the limits of knowledge 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 useful insight for making technology development resource allocation decisions. PMID:11538570

  11. 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

  12. 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.

  13. Decision support framework for developing regional energy strategies.

    PubMed

    Bessette, Douglas L; Arvai, Joseph; Campbell-Arvai, Victoria

    2014-01-01

    In an effort to reduce "carbon pollution" as well as prepare the U.S. for the impacts of climate change, President Obama's 2013 Climate Action Plan calls for changes to be made to the nation's energy system. In addition to focusing on alternative portfolios of different fuels and power-generation technologies, researchers and advisory panels have urged that changes to the nation's energy system be based on a decision-making framework that incorporates stakeholders and accounts for real-world resource, supply, and demand constraints. To date, research and development on such a framework have proven elusive. The research reported here describes the development and test of a potential decision support framework that combines elements from structured decision-making (SDM) with portfolio analysis, methods that have been used independently to elicit preferences in complex decision contexts. This hybrid framework aimed to (1) provide necessary background information to users regarding the development of coupled climate-energy strategies; (2) account for users' values and objectives; (3) allow for the construction of bespoke energy portfolios bounded by real-world supply and demand constraints; and (4) provide a more rigorous basis for addressing trade-offs. Results show that this framework was user-friendly, led to significant increases in users' knowledge about energy systems and, importantly, led to more internally consistent decisions. For these reasons, this framework may serve as a suitable template for supporting decisions about energy transitions in the United States and abroad. PMID:24400710

  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. Knowingplant: decision support and planning for engineering design

    NASA Astrophysics Data System (ADS)

    Haeberle, Stephan; Fuerst, Karl

    2000-10-01

    In this paper a software tool for engineering design is presented, which supports the user in drafting automation tasks. The system was developed in cooperation with an industrial partner to assist sales representatives of components for automation (like linear drives, grippers, etc.). Today, sales representatives are supported with information on components in the form of paper catalogs or CD-ROMs, but although they do not sell complete systems, they need structured in formation on tasks and standards to meet their consulting obligation. Knowingplant provides a framework to structure and document automation knowledge in a hierarchical network of functions, where a function can be described as an automation task like temperature measuring. Each of these functions is either described by a set of sub function or can be refined by a decision between alternative functions. The decision making process is supported by decision tables and a search for similar decision problems on the base of parameter values. On the base of the hierarchical knowledge representation projects are drafted. Functions used in projects are automatically transferred together with their sub-functions until the system reaches a decision, which have to be made by the user. This leads to a fast structured draft of projects with all related subtasks and required parameters for further indoor processing. Knowingplant provides a flexible framework for system users as well as for knowledge authors who can easily update represented knowledge without programming, which enables a continuous growing knowledge base.

  16. 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.

  17. Improving Agreement About Intervention Plans in Probation by Decision Support.

    PubMed

    Bosker, Jacqueline; Witteman, Cilia; Hermanns, Jo; Heij, Donnalee

    2015-12-01

    Reliability in decision making about intervention plans is a necessary condition for evidence-based probation work and equal treatment of offenders. Structuring decision making can improve agreement between clinical decision makers. In a former study however, we found that in Dutch probation practice structured risk and needs assessment did not result in acceptable agreement about intervention plans. The Dutch probation services subsequently introduced a tool for support in decision making on intervention plans. This article addresses the question whether the use of this tool results in better agreement between probation officers. A significant and meaningful improvement in agreement was found on all domains of the intervention plan. Implications for probation practice are discussed. PMID:24927740

  18. Model-based decision support in diabetes care.

    PubMed

    Salzsieder, E; Vogt, L; Kohnert, K-D; Heinke, P; Augstein, P

    2011-05-01

    The model-based Karlsburg Diabetes Management System (KADIS®) has been developed as a patient-focused decision-support tool to provide evidence-based advice for physicians in their daily efforts to optimize metabolic control in diabetes care of their patients on an individualized basis. For this purpose, KADIS® was established in terms of a personalized, interactive in silico simulation procedure, implemented into a problem-related diabetes health care network and evaluated under different conditions by conducting open-label mono- and polycentric trials, and a case-control study, and last but not least, by application in routine diabetes outpatient care. The trial outcomes clearly show that the recommendations provided to the physicians by KADIS® lead to significant improvement of metabolic control. This model-based decision-support system provides an excellent tool to effectively guide physicians in personalized decision-making to achieve optimal metabolic control for their patients. PMID:20621384

  19. 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.

  20. Using a Group Decision Support System as a Teaching Tool.

    ERIC Educational Resources Information Center

    Aiken, Milam W.

    1992-01-01

    Describes a typical Group Decision Support System (GDSS) in use at the University of Mississippi and potential uses of a GDSS in seminars, interactive testing, lectures, foreign language study, and in communication with deaf or mute students. Benefits are noted, including increased participation, group synergy, and automated record keeping. (27…

  1. Decision Support Systems and the Art of Enrollment Management.

    ERIC Educational Resources Information Center

    Beeler, Karl J.

    1989-01-01

    Summarizes college enrollment management process and its inherent information requirements, followed by section on the limitations of traditional management information systems (MIS). Introduces decision support systems, emphasizing the improvement of MIS applications in the enrollment management process. Underscores competitive nature of…

  2. 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…

  3. 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 ...

  4. OASIS: A GRAPHICAL DECISION SUPPORT SYSTEM FOR GROUNDWATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system far ground-water contaminant modeling. raphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces....

  5. 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 (...

  6. Using Clinical Decision Support Software in Health Insurance Company

    NASA Astrophysics Data System (ADS)

    Konovalov, R.; Kumlander, Deniss

    This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.

  7. Decision Support System Development for the Treatment of Maladaptive Behaviors.

    ERIC Educational Resources Information Center

    Hile, Matthew G.; Desrochers, Marcie N.

    The Mental Retardation-Expert (MR-E) is a microcomputer based expert decision support system that provides practitioners with state of the art assistance in the treatment of aggressive, self injurious, and destructive behaviors displayed by individuals with mental retardation or developmental disabilities. This system, based on human experts and…

  8. 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…

  9. 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...

  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. 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

  12. 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

  13. A decision support system to determine optimal ventilator settings

    PubMed Central

    2014-01-01

    Background Choosing the correct ventilator settings for the treatment of patients with respiratory tract disease is quite an important issue. Since the task of specifying the parameters of ventilation equipment is entirely carried out by a physician, physician’s knowledge and experience in the selection of these settings has a direct effect on the accuracy of his/her decisions. Nowadays, decision support systems have been used for these kinds of operations to eliminate errors. Our goal is to minimize errors in ventilation therapy and prevent deaths caused by incorrect configuration of ventilation devices. The proposed system is designed to assist less experienced physicians working in the facilities without having lung mechanics like cottage hospitals. Methods This article describes a decision support system proposing the ventilator settings required to be applied in the treatment according to the patients’ physiological information. The proposed model has been designed to minimize the possibility of making a mistake and to encourage more efficient use of time in support of the decision making process while the physicians make critical decisions about the patient. Artificial Neural Network (ANN) is implemented in order to calculate frequency, tidal volume, FiO2 outputs, and this classification model has been used for estimation of pressure support / volume support outputs. For the obtainment of the highest performance in both models, different configurations have been tried. Various tests have been realized for training methods, and a number of hidden layers mostly affect factors regarding the performance of ANNs. Results The physiological information of 158 respiratory patients over the age of 60 and were treated in three different hospitals between the years 2010 and 2012 has been used in the training and testing of the system. The diagnosed disease, core body temperature, pulse, arterial systolic pressure, diastolic blood pressure, PEEP, PSO2, pH, pCO2

  14. 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

  15. 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.

  16. Commercial pharmacogenetic-based decision-support tools in psychiatry.

    PubMed

    Bousman, Chad A; Hopwood, Malcolm

    2016-06-01

    Despite a compendium of pharmacotherapies available for treating psychiatric illnesses, suboptimal response to these therapies is typical and thought to be in part a result of genetic variation. This notion has sparked a personalised psychiatry movement, which has in turn led to the development of several commercial pharmacogenetic-based decision support tools marketed to psychiatrists as an alternative to typical, trial-and-error, prescribing. However, there is considerable uncertainty about the validity and usefulness of these tools and whether there is sufficient evidence to support their adoption. In this Personal View, we provide an introduction to these tools and assess their potential usefulness in psychiatry practice. We conclude with clinical considerations and development strategies for improving future pharmacogenetic-based decision support tools for clinical use. PMID:27133546

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. Using multiple criteria decision analysis for supporting decisions of solid waste management.

    PubMed

    Cheng, Steven; Chan, Christine W; Huang, Guo H

    2002-01-01

    Design of solid-waste management systems requires consideration of multiple alternative solutions and evaluation criteria because the systems can have complex and conflicting impacts on different stakeholders. Multiple criteria decision analysis (MCDA) has been found to be a fruitful approach to solve this design problem. In this paper, the MCDA approach is applied to solve the landfill selection problem in Regina of Saskatchewan Canada. The systematic approach of MCDA helps decision makers select the most preferable decision and provides the basis of a decision support system. The techniques that are used in this study include: 1) Simple Weighted Addition method, 2) Weighted Product method, 3) TOPSIS, 4) cooperative game theory, and 5) ELECTRE. The results generated with these methods are compared and ranked so that the most preferable solution is identified. PMID:12090287

  2. Integrated assessment for supporting decision making with multiple criteria

    NASA Astrophysics Data System (ADS)

    Friedrich, R.

    2015-08-01

    Decisions about the development of the energy system should take all relevant criteria into account, including costs and health, environmental and climate impacts. As usually no decision alternative fulfils all criteria better than all other alternatives, a weighting between the indicators that show the degree of fulfilment of the criteria, is necessary. In the following the "impact pathway approach" is described that supports decisions by using weighting factors that are derived from measuring or observing the preferences of the population. The methodology is applied to rank technologies for generating electricity according to their social costs, which is a summary indicator comprising simultaneously costs, impacts of air pollution on health and biodiversity and climate impacts.

  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. 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.

  6. Cotton Modeling for Climate Change, On-farm Decision Support, and Policy Decisions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop simulation models are valuable tools that scientists can use in testing hypothesis. Models also are used to identify the areas where knowledge is lacking, indicating the needs for future research activities. In addition, models are being used as decision support systems at the farm level to opt...

  7. 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…

  8. 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.

  9. 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

  10. Overcoming barriers to development of cooperative medical decision support models.

    PubMed

    Hudson, Donna L; Cohen, Maurice E

    2012-01-01

    Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers. PMID:23366358

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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. PMID:22874401

  16. Web-based health services and clinical decision support.

    PubMed

    Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

    2004-01-01

    The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase. PMID:15718591

  17. Clinical Decision Support for Vascular Disease in Community Family Practice

    PubMed Central

    Keshavjee, K; Holbrook, AM; Lau, E; Esporlas-Jewer, I; Troyan, S

    2006-01-01

    The COMPETE III Vascular Disease Tracker (C3VT) is a personalized, Web-based, clinical decision support tool that provides patients and physicians access to a patient’s 16 individual vascular risk markers, specific advice for each marker and links to best practices in vascular disease management. It utilizes the chronic care model1 so that physicians can better manage patients with chronic diseases. Over 1100 patients have been enrolled into the COMPETE III study to date.

  18. 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.

  19. 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)

  20. Teaching medical diagnosis: a rule-based approach.

    PubMed

    Michalowski, W; Rubin, S; Aggarwal, H

    1993-01-01

    This paper discusses the design of a diagnostic process simulator which teaches medical students to think clinically. This was possible to achieve due to the application of a rule-based approach to represent diagnosis and treatments. Whilst using the simulator, as a result of the student's incorrect and correct decisions, the clinical situation changes accordingly. New diagnostic options result in the ability to choose further clinical and laboratory tests. The simulator is being implemented on Sun workstations and Macintosh computers using Prolog programming language. PMID:8139404

  1. 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

  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. Design of a Decision Support System to Help Clinicians Manage Glycemia in Patients with Type 2 Diabetes Mellitus

    PubMed Central

    Rodbard, David; Vigersky, Robert A

    2011-01-01

    Objective We sought to develop a computerized clinical decision support for clinicians treating patients with type 2 diabetes mellitus (T2DM). Methods We designed, developed, and tested a computer-assisted decision support (CADS) system using statistical analyses of self-monitoring of blood glucose data, laboratory data, medical and medication history, and individualized hemoglobin A1c goals. A rule-based expert system generated recommendations for changes in therapy and accompanying explanations. Results A clinical decision support system (CADS) was developed that considers 9 classes of medications and 69 regimens with combinations of up to 4 therapeutic agents. The preferred sequences of regimens can be customized. The program is integrated with a “comprehensive diabetes management system,” electronic medical record systems, and a method for uploading data from memory glucose meters via telephone without use of a computer or the Internet. The software provides a report to the clinician regarding the overall quality of glycemic control and identifies problems, e.g., hypoglycemia, hyperglycemia, glycemic variability, and insufficient data. The program can recommend continuation of current therapy, adjustment of dosages of current medications, or change of regimen and can provide explanations for its recommendations. If the user rejects the recommendations, the program will recommend alternative approaches. The CADS also provides access to Food and Drug Administration-approved prescribing information, guidelines from professional organizations, and selections from the general medical literature. The system has been extensively tested with real and synthetic data and is ready for evaluation in multicenter clinical trials. Conclusion A clinical decision support system to assist with the management of patients with T2DM was designed, developed, tested, and found to perform well. PMID:21527112

  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. 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.

  8. 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.

  9. 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.

  10. A Systematic Approach for Climate Change Decision Support

    NASA Astrophysics Data System (ADS)

    Kumar, S.; Cantrell, S. J.; Higgins, G. J.; Vanwijngaarden, F.

    2010-12-01

    To effectively predict and prepare for the effects of global climate change on the worldwide population, infrastructure and economy, we need to take a quantum leap forward in how we deal with the issue. Those who must make climate-sensitive decisions need access to the best available climate science information and analysis. To overcome barriers and change behavior, the information must be credible, robust, unbiased, and based on research results that are broadly accepted by the climate science community. Moreover, the process for delivery of information must be tailored to the users’ needs and practices. Unfortunately, much of climate science data today is in the “science domain”, and not available to end users in a form they can use to take action. So there is a need to bridge the gap and take a systematic approach driven by user requirements to sharing climate change science research and analysis with decision makers that would enable them to develop adaptation and mitigation strategies. These needs will become all the more pressing as climate change information is used in real world decisions involving the commitment of large resources and with potential liability and litigation. In this paper, we describe an approach that involves multidisciplinary cooperation and systematic integration of climate change data acquisition and management, climate modeling and projections, uncertainty quantification and risk assessments, economic analysis, and decision support delivered through customized user interfaces.

  11. 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. PMID:17434170

  12. 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.

  13. Decision Integration and Support Engine (DISE) for dynamic aircraft and ISR asset tasking/retasking decision support for the AOC

    NASA Astrophysics Data System (ADS)

    VonPlinsky, Michael J.; Crowder, Ed

    2002-07-01

    The Decision Integration and Support Environment (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision processes. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosecuted, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process. DISE, when running in its constructive mode, automatically selects the best-suited aircraft and assigns the new target. In virtual mode, with a human operator, DISE presents the user with a suitability ranked list of the available aircraft for assignment. Recent DISE enhancements are applying this concept to the prioritization and scheduling of ISR support requests from Users to support both latent and dynamic tasking and scheduling of both space-based and airborne ISR assets.

  14. 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.

  15. 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.

  16. 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.

  17. Technosocial Predictive Analytics in Support of Naturalistic Decision Making

    SciTech Connect

    Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.; Riensche, Roderick M.; Thomas, James J.; Unwin, Stephen D.; Whitney, Paul D.; Wong, Pak C.

    2009-06-23

    A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledge management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.

  18. 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

  19. Computerized decision support in adult and pediatric critical care

    PubMed Central

    Williams, Cydni N; Bratton, Susan L; Hirshberg, Eliotte L

    2013-01-01

    Computerized decision support (CDS) is the most advanced form of clinical decision support available and has evolved with innovative technologies to provide meaningful assistance to medical professionals. Critical care clinicians are in unique environments where vast amounts of data are collected on individual patients, and where expedient and accurate decisions are paramount to the delivery of quality healthcare. Many CDS tools are in use today among adult and pediatric intensive care units as diagnostic aides, safety alerts, computerized protocols, and automated recommendations for management. Some CDS use have significantly decreased adverse events and improved costs when carefully implemented and properly operated. CDS tools integrated into electronic health records are also valuable to researchers providing rapid identification of eligible patients, streamlining data-gathering and analysis, and providing cohorts for study of rare and chronic diseases through data-warehousing. Although the need for human judgment in the daily care of critically ill patients has limited the study and realization of meaningful improvements in overall patient outcomes, CDS tools continue to evolve and integrate into the daily workflow of clinicians, and will likely provide advancements over time. Through novel technologies, CDS tools have vast potential for progression and will significantly impact the field of critical care and clinical research in the future. PMID:24701413

  20. Decision support using the Multistatic Tactical Planning Aid (MSTPA)

    NASA Astrophysics Data System (ADS)

    Strode, Christopher; Mourre, Baptiste; Rixen, Michel

    2012-01-01

    The Multistatic Tactical Planning Aid (MSTPA) is a tool currently in development at NATO Undersea Research Centre which may be used to model the performance of a given multistatic sensor network in terms of the probability of detection of a submarine, the ability to hold a track and whether such a track could be correctly classified as such. The tool therefore considers the entire chain of events from an initial calculation of signal excess, the generation of a contact considering localisation errors, followed by the subsequent tracking and classification process. In its current form, the tool may be used to plan a particular multistatic scenario through operational analysis of many Monte Carlo simulations. The future development of MSTPA will transition towards a real-time decision support tool to assist operators and planners at sea. This study introduces a number of generic decision support techniques which may be wrapped around the MSTPA tool. The acoustic performance metric that will drive decisions will of course be subject to uncertainty relating to environmental measurements and extrapolations. The effect of this uncertainty on acoustic performance is examined here. Future studies will consider the sensitivity of the eventual decision—in terms of optimum sensor positions—to the acoustic uncertainty.

  1. 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

  2. Dynamic clinical data mining: search engine-based decision support.

    PubMed

    Celi, Leo Anthony; Zimolzak, Andrew J; Stone, David J

    2014-01-01

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients. PMID:25600664

  3. Creating Shareable Decision Support Services: An Interdisciplinary Challenge

    PubMed Central

    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. PMID:21347049

  4. 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.

  5. Dynamic Clinical Data Mining: Search Engine-Based Decision Support

    PubMed Central

    Zimolzak, Andrew J; Stone, David J

    2014-01-01

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients. PMID:25600664

  6. Clinical decision support systems: data quality management and governance.

    PubMed

    Liaw, Siaw-Teng

    2013-01-01

    This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. The scope of DQM & IG should range from data creation and collection in clinical settings, through cleaning and, where obtained from multiple sources, linkage, storage, use by the EDS logic engine and algorithms, knowledge base and guidance provided, to curation and presentation. It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care. PMID:24018528

  7. Malaria elimination: moving forward with spatial decision support systems.

    PubMed

    Kelly, Gerard C; Tanner, Marcel; Vallely, Andrew; Clements, Archie

    2012-07-01

    Operational challenges facing contemporary malaria elimination have distinct geospatial elements including the need for high-resolution location-based surveillance, targeted prevention and response interventions, and effective delivery of essential services at optimum levels of coverage. Although mapping and geographical reconnaissance (GR) has traditionally played an important role in supporting malaria control and eradication, its full potential as an applied health systems tool has not yet been fully realised. As accessibility to global positioning system (GPS), geographic information system (GIS) and mobile computing technology increases, the role of an integrated spatial decision support system (SDSS) framework for supporting the increased operational demands of malaria elimination requires further exploration, validation and application; particularly in the context of resource-poor settings. PMID:22607693

  8. Computer-Based Medical Decision Support System based on guidelines, clinical pathways and decision nodes.

    PubMed

    Tomaszewski, Wiesław

    2012-01-01

    A continuous and dynamic development of medical sciences which is currently taking place all over the world is associated with a considerable increase in the number of scientific reports and papers of importance in enhancing the effectiveness of treatment and quality of medical care. However, it is difficult, or, indeed, impossible, for physicians to regularly follow all recent innovations in medical knowledge and to apply the latest research findings to their daily clinical practice. More and more studies conducted both in Poland and worldwide as well as experience from clinical practice in various countries provide convincing evidence that various systems supporting medical decision-making by physicians or other medical professionals visibly improve the quality of medical care. The use of such systems is already possible and recently has been developing especially dynamically, as the level of knowledge and information and communication technology now permits their effective implementation. Currently, electronic knowledge bases, together with inference procedures, form intelligent medical information systems, which offer many possibilities for the support of medical decision-making, mainly in regard to interactive diagnostic work-up, but also the selection of the most suitable treatment plan (clinical pathway). Regardless of their scale and area of application, these systems are referred to as Computer-Based Medical Decision Support Systems (CBMDSS). PMID:22741924

  9. 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

  10. 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.

  11. 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.

  12. [ Preventing adverse drug events using clinical decision support systems].

    PubMed

    Salili, Ali Reza; Hammann, Felix; Taegtmeyer, Anne B

    2015-12-01

    Adverse drug events pose a great risk to patients, are an everyday clinical problem and can have potential/ega/ consequences. Computerized physician order entry or computerized provider order entry (CPOE} in combination with clinical decision support systems {CDSS) are popular and aim to reduce prescribing errors as well as identifying potentially harmful drug drug interactions. The quantifiable benejit these systems bring to patients, has however, yet to be definitively proven. This article focusses on the current standpoint of CPOE-/CDSS, their risks and benefits, the potential for improvement and their perspectives for the future. PMID:26654813

  13. 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

  14. 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. PMID:22874282

  15. Development of a decision support system for cost analysis.

    PubMed

    Chae, Y M

    1989-01-01

    Korean hospitals are experiencing an increasing amount of financial difficulty due to government control of hospital rates since national health insurance has been implemented. The decision support system (DSS) was developed to provide cost and revenue information for the services rendered by each department in an effort to reduce costs. This information may be used to identify the causes of financial loss if cost exceeds revenue and to develop budgets for the next year. The DSS was developed using a micromainframe interface approach where the mainframe computer collects and summarises daily cost data and the micro computer allocates the data to each department. PMID:10304295

  16. Multiple Perspectives on the Meaning of Clinical Decision Support

    PubMed Central

    Richardson, Joshua E.; Ash, Joan S.; Sittig, Dean F.; Bunce, Arwen; Carpenter, James; Dykstra, Richard H.; Guappone, Ken; McCormack, James; McMullen, Carmit K.; Shapiro, Michael; Wright, Adam; Middleton, Blackford

    2010-01-01

    Clinical Decision Support (CDS) is viewed as a means to improve safety and efficiency in health care. Yet the lack of consensus about what is meant by CDS represents a barrier to effective design, implementation, and utilization of CDS tools. We conducted a multi-site qualitative inquiry to understand how different people define and describe CDS. Using subjects’ multiple perspectives we were able to gain new insights as to what stakeholders want CDS to achieve and how to achieve it even when those perspectives are competing and conflicting. PMID:21347119

  17. Multiple Perspectives on the Meaning of Clinical Decision Support

    PubMed Central

    Richardson, Joshua E.; Ash, Joan S.; Sittig, Dean F.; Bunce, Arwen; Carpenter, James; Dykstra, Richard H.; Guappone, Ken; McMullen, Carmit K.; Shapiro, Michael; Wright, Adam

    2010-01-01

    Clinical Decision Support (CDS) is viewed as a means to improve safety and efficiency in health care. Yet the lack of a consensus around what is meant by CDS represents a barrier to effective design, use, and utilization of CDS tools. We conducted a multi-site qualitative inquiry to understand how different people define and describe CDS. Using subjects’ multiple perspectives we were able to gain new insights as to what stakeholders want CDS to achieve and how to achieve it; even at times when those perspectives are competing and conflicting. PMID:21347063

  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. 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.

  20. Surveillance video with spatially registered graphics for decision support

    NASA Astrophysics Data System (ADS)

    Majoros, Anthony; Ianni, John; Davies, Paul; Higgins, Robert; Havig, Paul

    2007-04-01

    Conventional daylight video, and other forms of motion imagery, have an expanded role in communication and decision making as sensor platforms (e.g., unoccupied aerial vehicles [UAVs]) proliferate. Video, of course, enables more persons to become observers than does direct viewing, and presents a rapidly growing volume of content for those observers to understand and integrate. However, knowing the identity of objects and gaining an awareness of situations depicted in video can be challenging as the number of camera feeds increases, or as multiple decision makers rely on the same content. Graphic additions to streaming video, spatially registered and appearing to be parts of the observed scene, can draw attention to specific content, reduce uncertainty, increase awareness of evolving situations, and ultimately produce a type of image-based communication that reduces the need for verbal interaction among observers. This paper describes how streaming video can be enhanced for decision support using feature recognition and tracking; object identification, graphic retrieval and positioning; and collaborative capabilities.

  1. Animated simulation: a valuable decision support tool for practice improvement.

    PubMed

    Ledlow, G R; Bradshaw, D M

    1999-01-01

    Animated computer simulation is a powerful tool for healthcare operation improvement. As a decision support tool, it offers a systematic method to compare alternative approaches to healthcare operations. Because staff interaction is encouraged by this tool, simulation projects facilitate staff team building and process change ownership. Information that is not used as applied knowledge for the purpose of improvement is worthless. Simulation offers management detailed knowledge of processes, enabling management to make better-informed decisions by providing performance data, such as resource usage rates, patient wait times, capacity rates, and process performance information. Alternatives under consideration can be compared and modified without high financial, personal, and customer costs to the healthcare operation. The knowledge gained from each alternative's simulation response variables can be evaluated against set criteria, the status quo, and each other to determine the best option. Current automation systems and software products allow decision makers to use this tool without investing resources in errant options. A simulation project strategy with examples and a case study of change and renovation of a family practice clinic are provided. PMID:10350840

  2. Design of a decision support system in disaster management

    SciTech Connect

    Therrien, M.C.; Wybo, J.L.

    1995-12-31

    When a disaster occurs, complexity, turbulence and often uncertainty about crucial information and organization make coordination and decisions difficult. Managers faced with emergencies have several ways to take decision: from predefined plans associated to identified emergencies, from acquired knowledge linking observation to danger evaluation and related strategies, instantly, from no experience at all, from experience of past disasters and case studies. Disaster management is complex because each organization has its own regulations, practices and culture, and because managers are not aware of all the knowledge and experience of colleagues from other organizations. To improve efficiency, organizations such as the International Red Cross are designing and implementing global information systems and databases, to make possible an efficient sharing of information and to make available this experience in disaster management. This study has been started to propose a decision support system; the goal is to help any disaster manager by exploiting all the experience of disaster management which is available, using Artificial Intelligence techniques to assess similarities between disasters and to benefit from disasters experienced in the past.

  3. Decision support system for the analysis of hospital operation indicators.

    PubMed

    Wu, Fan; Lin, Jiunn Rong; Tsai, Wen-Chen

    2002-12-01

    The inauguration of national health insurance (NHI) in many countries and their worsening financial condition has increased the sensitivity to operational cost and efficiency in hospitals. For several years, hospitals have been monitoring their operations by analyzing the financial and operational reports that are provided. Because of the rapidly changing character of the medical industry, statistical data shown on paper are no longer sufficient for decision makers. This paper describes a decision support system (DSS) for hospital administrators to assist in analyzing their operations efficiently and precisely. In hospitals, operational data of outpatients and inpatients are now stored on computers, resulting in much easier and faster data acquisition for administrators. The proposed system makes suggestions to hospital administrators and is able to self-learn to improve its future usefulness. With the dual capabilities of integrating evaluations and data collecting, the system can assist administrators in discovering and resolving problems quickly. The system provides multidimensional and multilevel analyses, by using data warehousing techniques, and generates appropriate advice to users by employing decision-making methodology. The self-learning function of the system makes it work like an expert, continually modifying its content (knowledge) and generating advice that is promptly updated to accord with changes in the medical industry. PMID:12594099

  4. 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.

  5. Ecosystem Services Reseach Program: LTG 1: Integration, decision support, human well being and outreach

    EPA Science Inventory

    Decision support is the goal, and measurable endpoint, for the program; to enable decision makers to use ecosystem services in decisions to achieve improved environmental outcomes. It includes the science of decision support, human well-being research, valuation of services, out...

  6. Parallelism In Rule-Based Systems

    NASA Astrophysics Data System (ADS)

    Sabharwal, Arvind; Iyengar, S. Sitharama; de Saussure, G.; Weisbin, C. R.

    1988-03-01

    Rule-based systems, which have proven to be extremely useful for several Artificial Intelligence and Expert Systems applications, currently face severe limitations due to the slow speed of their execution. To achieve the desired speed-up, this paper addresses the problem of parallelization of production systems and explores the various architectural and algorithmic possibilities. The inherent sources of parallelism in the production system structure are analyzed and the trade-offs, limitations and feasibility of exploitation of these sources of parallelism are presented. Based on this analysis, we propose a dedicated, coarse-grained, n-ary tree multiprocessor architecture for the parallel implementation of rule-based systems and then present algorithms for partitioning of rules in this architecture.

  7. 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

  8. 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.…

  9. 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

  10. Evaluation of RxNorm for Medication Clinical Decision Support.

    PubMed

    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