Science.gov

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. 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.

  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. 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

  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. The conceptual foundation of environmental decision support.

    PubMed

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

    2015-05-01

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

  10. 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.

  11. 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.

  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. 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.

  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. 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.

  17. 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.

  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 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

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

    PubMed

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

    2015-01-01

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

  8. 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 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.

  13. 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

  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. 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

  3. 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.

  4. 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.

  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. 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)

  9. 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...

  10. 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.

  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. 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

  15. 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

  16. 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

  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. 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.

  11. 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

  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. 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.

  15. 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

  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. 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

  1. 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

  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. 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.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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.

  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. 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…

  1. 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 ...

  2. 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....

  3. 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 (...

  4. 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.

  5. 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…

  6. 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…

  7. 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...

  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. 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…

  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. 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.

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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.

  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. 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.

  17. 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

  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. 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

  20. 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.

  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. 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)

  3. 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

  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. 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.

  6. 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

  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. 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

  10. 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.

  11. 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.

  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. North Slope Decision Support for Water Resource Planning and Management

    SciTech Connect

    Schnabel, William; Brumbelow, Kelly

    2013-03-31

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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  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. 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

  1. 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

  2. Decision System Integrating Preferences to Support Sleep Staging.

    PubMed

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

    2016-01-01

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

  3. 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.

  4. 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

  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. 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

  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. 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

  13. 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

  14. 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

  15. 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

  16. [ 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

  17. 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

  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. 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

  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. 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.

  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. 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

  7. 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.…

  8. 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.

  9. Evaluation of RxNorm for Medication Clinical Decision Support

    PubMed Central

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

    2014-01-01

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

  10. 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

  11. 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

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

    PubMed

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

    1992-01-01

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

  13. Decision Support for Integrated Energy-Water Planning

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  14. Integrated Decision Support for Global Environmental Change Adaptation

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  15. [Use of spreadsheets as decision support systems in health care].

    PubMed

    Sabanović, Z; Masic, I

    1995-01-01

    During the last decade the spreadsheets take very important place in many different kind of theoretical and practical applications. In recent years the PC-Windows Operating System allowed us to use and develop many sorts of specialised software packages, as well as expert packages, applicable in medicine. The relationship or communication between man and computer has been improved using new hardware configuration based on fast and intelligent processors, software modification and audio-visual technology. The facts mentioned above have instantly produced circumstances for more powerful spreadsheet software. According to powerful spreadsheet features we can utilise calculation and maximise HIGM requirement for our software configuration. The investigation within large area of Tuzla-Podrinje Kanton shows us that small number of people are using spreadsheet in medical application. Very small percentage of people have limited number of applications on calculation like, subtraction, addition, multiplication, division and percentage. They have often used spreadsheet as an integral part of the following software packages, EXCEL ver. 5.0 and very little Lotus 1-2-3 because Lotus is in these days behind. The aim of this paper is to highlight application of the spreadsheet USING EXCEL software package. Apart from simple calculation and graphic presentation in "DSS-Decision making support system" can be used for model simulation, generator configuration, management monitoring, support and decision making in health care. PMID:9324558

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

    PubMed

    Richards, Bernard

    2013-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  20. Decision support system for diabetic retinopathy using discrete wavelet transform.

    PubMed

    Noronha, K; Acharya, U R; Nayak, K P; Kamath, S; Bhandary, S V

    2013-03-01

    Prolonged duration of the diabetes may affect the tiny blood vessels of the retina causing diabetic retinopathy. Routine eye screening of patients with diabetes helps to detect diabetic retinopathy at the early stage. It is very laborious and time-consuming for the doctors to go through many fundus images continuously. Therefore, decision support system for diabetic retinopathy detection can reduce the burden of the ophthalmologists. In this work, we have used discrete wavelet transform and support vector machine classifier for automated detection of normal and diabetic retinopathy classes. The wavelet-based decomposition was performed up to the second level, and eight energy features were extracted. Two energy features from the approximation coefficients of two levels and six energy values from the details in three orientations (horizontal, vertical and diagonal) were evaluated. These features were fed to the support vector machine classifier with various kernel functions (linear, radial basis function, polynomial of orders 2 and 3) to evaluate the highest classification accuracy. We obtained the highest average classification accuracy, sensitivity and specificity of more than 99% with support vector machine classifier (polynomial kernel of order 3) using three discrete wavelet transform features. We have also proposed an integrated index called Diabetic Retinopathy Risk Index using clinically significant wavelet energy features to identify normal and diabetic retinopathy classes using just one number. We believe that this (Diabetic Retinopathy Risk Index) can be used as an adjunct tool by the doctors during the eye screening to cross-check their diagnosis. PMID:23662341

  1. Aggregation of Environmental Model Data for Decision Support

    NASA Astrophysics Data System (ADS)

    Alpert, J. C.

    2013-12-01

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

  2. Devils Lake Climate, Weather, and Water Decision Support System

    NASA Astrophysics Data System (ADS)

    Horsfall, F. M.; Kluck, D. R.; Brewer, M.; Timofeyeva, M. M.; Symonds, J.; Dummer, S.; Frazier, M.; Shulski, M.; Akyuz, A.

    2010-12-01

    North Dakota’s Devils Lake area represents an example of a community struggling with a serious climate-related problem. The Devils Lake water level elevation has been rising since 1993 due to a prolonged wet period, and it is now approaching the spill stage into the Cheyenne River and ultimately into the Red River of the North. The impacts of the rising water have already caused significant disruption to the surrounding communities, and even greater impacts will be seen if the lake reaches the spill elevation. These impacts include flooding, water quality issues, impacts to agriculture and ecosystems, and impacts to local and regional economies. National Oceanic and Atmospheric Administration (NOAA), through the National Weather Service (NWS), the National Environmental Satellite, Data, and Information Service (NESDIS), and the Office of Oceanic and Atmospheric Research (OAR), provides the U.S. public with climate, water, and weather services, including meteorological, hydrological and climate data, warnings, and forecasts of weather and climate from near- to longer-term timescales. In support of the people of Devils Lake, the surrounding communities, the people of North Dakota, and the other Federal agencies with responsibilities in the area, NOAA launched the first ever climate-sensitive decision support web site (www.devilslake.noaa.gov) in July 2010. The website is providing integrated weather, water, and climate information for the area, and has links to information from other agencies, such as USGS, to help decision makers as they address this ongoing challenge. This paper will describe the website and other ongoing activities by NOAA in support of this community.

  3. Decision Support Systems and Management of The River Elbe

    NASA Astrophysics Data System (ADS)

    Wind, H. G.

    The European Community demands the development of a river basin management plan for all European rivers. The European Commission has also defined a number of objectives that must be met, for instance water quality etc. For a specific river additional objectives can be formulated for other functions which are satisfied by the river like shipping, nature, water quantity etc. The objectives can be regarded as a solution space. The objectives should be satisfied under criteria such as a safe transport of water, ice and sediment. The collection of measures can be seen as a measures space. In the plan of action of the river basin management plan is outlined by which set of measures (or by which part of the measures space) the present state should be transferred into the desired state. The selection of that set of measures which is acceptable for all relevant actors, is complicated by the various demands of the actors, knowledge about impacts of measures, availability of data and the impact of processes which are outside the borders of the system. In order to support this selection process, use can be made of a decision support system. For various rivers such as the Elbe and the Danube such a system is presently under construction. During the presentation some research questions related to the development of decision support systems will be outlined, such as: Integration of social systems, ecological systems and physical systems. Internal consistency of models, data and information demand. Time horizon related to the stiffness of the model system and the external developments. Information supply and information demand: a fallacy?

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  5. Dynamic adaptive learning for decision-making supporting systems

    NASA Astrophysics Data System (ADS)

    He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

    2008-03-01

    This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

  6. Merging Air Quality and Public Health Decision Support Systems

    NASA Astrophysics Data System (ADS)

    Hudspeth, W. B.; Bales, C. L.

    2003-12-01

    The New Mexico Air Quality Mapper (NMAQM) is a Web-based, open source GIS prototype application that Earth Data Analysis Center is developing under a NASA Cooperative Agreement. NMAQM enhances and extends existing data and imagery delivery systems with an existing Public Health system called the Rapid Syndrome Validation Project (RSVP). RSVP is a decision support system operating in several medical and public health arenas. It is evolving to ingest remote sensing data as input to provide early warning of human health threats, especially those related to anthropogenic atmospheric pollutants and airborne pathogens. The NMAQM project applies measurements of these atmospheric pollutants, derived from both remotely sensed data as well as from in-situ air quality networks, to both forecasting and retrospective analyses that influence human respiratory health. NMAQM provides a user-friendly interface for visualizing and interpreting environmentally-linked epidemiological phenomena. The results, and the systems made to provide the information, will be applicable not only to decision-makers in the public health realm, but also to air quality organizations, demographers, community planners, and other professionals in information technology, and social and engineering sciences. As an accessible and interactive mapping and analysis application, it allows environment and health personnel to study historic data for hypothesis generation and trend analysis, and then, potentially, to predict air quality conditions from daily data acquisitions. Additional spin off benefits to such users include the identification of gaps in the distribution of in-situ monitoring stations, the dissemination of air quality data to the public, and the discrimination of local vs. more regional sources of air pollutants that may bear on decisions relating to public health and public policy.

  7. A Collaborative Decision Environment to Support UAV Wildfire Monitoring Missions

    NASA Astrophysics Data System (ADS)

    Frost, C. R.; Enomoto, F. Y.; D'Ortenzio, M. V.; Nguyen, Q. B.

    2006-12-01

    NASA developed the Collaborative Decision Environment (CDE), the ground-based component of its Intelligent Mission Management (IMM) technology for science missions employing long endurance unmanned aerial vehicles (UAVs). The CDE was used to support science mission planning and decision-making for a NASA- and U.S. Forest Service-sponsored mission to monitor wildfires in the western United States using a multi- spectral imager flown onboard the General Atomics Altair UAV in summer of 2006. The CDE is a ground-based system that provides the mission/science team with situational awareness, collaboration, and decision tools. The CDE is used for pre-flight planning, mission monitoring, and visualization of acquired data. It integrates external data products used for planning and executing a mission, such as weather, large wildfire locations, satellite-derived fire detection data, temporarily restricted airspace, and satellite imagery. While a prototype CDE was developed as a Java-based client/server application in 2004-2005, the team investigated the use of Google Earth to take advantage of its 3-D visualization capabilities, friendly user interface, and enhanced graphics performance. External data is acquired via the Internet by leveraging established and emerging Open Geospatial Consortium (OGC) standards and is re-formatted into the Keyhole Markup Language (KML) specification used by Google Earth. Aircraft flight position and sensor data products are relayed from the instrument ground station to CDE servers where they are made available to users. An instant messaging chat server is used to facilitate real-time communication between remote users. This paper will present an overview of the CDE system architecture, and discuss how science user input was crucial to shaping and developing the system. Examples from the UAV mission will be used to illustrate the presentation. Plans for future development work to improve mission operations, such as integration with

  8. Mining multi-dimensional data for decision support

    SciTech Connect

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

    1998-06-01

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

  9. [Economic evaluation seeks threshold to support decision-making].

    PubMed

    García-Lorenzo, Borja; Vallejo-Torres, Laura; Trujillo-Martín, María Mar; Perestelo-Pérez, Lilisbeth; Valcárcel-Nazco, Cristina; Serrano Aguilar, Pedro

    2015-12-01

    To incorporate economic evaluation into decision-making, we need to know how much a health system is willing and able to invest in a quality-adjusted life year (QALY). In Spain, the figure of €30,000 per QALY as cost-effectiveness (CE) threshold has been widely cited. However, as in most health systems, no value has been formally adopted; mainly because of the arbitrariness, the lack of theoretical and scientific basis, and the controversy around its estimation and what the threshold should represent. Based on a systematic review of empirical studies on the estimation of the CE threshold undertaken by this research team, we conducted a critical appraisal of the state of the art, using a Delphi with the participation of 13 national experts. This paper contributes to assess the research progress on the CE threshold in Spain, to consider its utility in the decision making process supported by economic evaluation, and to propose further research to improve what has been achieved so far. PMID:26786302

  10. Decision support in medical practice: a physician's perspective

    NASA Astrophysics Data System (ADS)

    Shieh, Yao-Yang; Roberson, Glenn H.

    1998-03-01

    A physician's decision support system consists of three components: (1) a comprehensive patient record and medical knowledge database, (2) information infrastructure for data storage, transfer, and (3) an analytical inference engine, accompanied by business operation database. Medical knowledge database provides the guideline for the selection of powerful clinical features or tests to be observed so that an accurate diagnosis as well as effective treatment can be quickly reached. With a tremendous amount of information stored in multiple data centers, it takes an effective information infrastructure to provide streamlined flow of information to the physician in a timely fashion. A real-time analytical inference engine mimics the physician's reasoning process. However due to incomplete, imperfect data and medical knowledge, a realistic output from this engine will be a list of options with associated confidence level, expected risk, so that the physician can make a well-informed final decision. Physicians are challenged to pursue the objective of ensuring an acceptable quality of care in an economically restrained environment. Therefore, business operation data have to be factored into the calculation of overall loss. Follow-up of diagnosis and treatment provides retrospective assessment of the accuracy and effectiveness of the existing inference engine.

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

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

    PubMed

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

    1995-01-01

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

  13. Metaphor graphics to support integrated decision making with respiratory data.

    PubMed

    Cole, W G; Stewart, J G

    1993-05-01

    Support for data integration in the intensive care unit (ICU) often includes efforts to improve the display of data. An electronic version of a flowsheet (table of numbers) with optimal line graphs is by far the most common format in current ICU computer workstation technology, yet there is little evidence that this format provides particularly good support for human integration of data. The present work introduces a new form of graphic representation, one that is far more metaphoric, far more tailored to the intensive care unit than a line graph. This graphic system, called volume rectangles represents mechanical ventilator data in such a way that is easy to keep different types of variables conceptually separated, yet easy to see how they relate in a truly integrated way. Volume rectangles are one example of a general approach to display of data called the metaphor graphic approach, which is being evaluated in this and other contexts. Metaphor graphics are custom tailored visual displays designed to look like the real world situation from which the data is collected but not in a literal sense of 'look like'. Anecdotal observation suggests that such graphics are easy to learn, are remembered over long period, and are good decision support tools when the task is finding patterns in a mass of data. PMID:8366316

  14. Clinical decision support for perioperative information management systems.

    PubMed

    Wanderer, Jonathan P; Ehrenfeld, Jesse M

    2013-12-01

    Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered. PMID:23690340

  15. Decision Support Systems for Launch and Range Operations Using Jess

    NASA Technical Reports Server (NTRS)

    Thirumalainambi, Rajkumar

    2007-01-01

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

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

    SciTech Connect

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

    2012-06-12

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

  17. NOAA Climate Information and Tools for Decision Support Services

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  18. Clinical decision support for physician order-entry: design challenges.

    PubMed

    Broverman, C A; Clyman, J I; Schlesinger, J M; Want, E

    1996-01-01

    We report on a joint development effort between ALLTEL Information Services Health Care Division and IBM Worldwide Healthcare Industry to demonstrate concurrent clinical decision support using Arden Syntax at order-entry time. The goal of the partnership is to build a high performance CDS toolkit that may be easily customized for multiple health care enterprises. Our work uses and promotes open technologies and health care standards while building a generalizable interface to a legacy patient-care system and clinical database. This paper identifies four areas of design challenges and solutions unique to a concurrent order-entry environment: the clinical information model, the currency of the patient virtual chart, the granularity of event triggers and rule evaluation context, and performance. PMID:8947731

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

    PubMed

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

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

  20. Spatio-temporal Visualization for Environmental Decision Support

    SciTech Connect

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

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Scott, C. A.

    2015-12-01

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

  2. Decision support systems and methods for complex networks

    DOEpatents

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

    2012-02-28

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

  3. Child Welfare Workers’ Adoption of Decision Support Technology

    PubMed Central

    Foster, Kirk A.; Stiffman, Arlene R.

    2009-01-01

    Child welfare workers must process complex information in deciding to refer clients to appropriate mental health services. Decision support systems (DSS) have been demonstrated in other fields to be an important tool, yet little research has been done in child welfare. This study focused on the adoption of a specific DSS into child welfare practice. Quantitative analysis was used to demonstrate the diffusion of innovation process among a sample of state child welfare workers, while qualitative analysis was used to explain the facilitators and barriers to DSS adoption. Results indicate that for DSSs to be widely adopted in child welfare practice, they should be integrated into the referral system and include workers’ knowledge and experiences with referral resources. For successful adoption, DSSs need to respect the natural logic and flow of worker interaction, as well as organizational constraints. PMID:20198123

  4. New decision support tool for acute lymphoblastic leukemia classification

    NASA Astrophysics Data System (ADS)

    Madhukar, Monica; Agaian, Sos; Chronopoulos, Anthony T.

    2012-03-01

    In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

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

    PubMed

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

    2013-01-01

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

  6. A Clinical Decision Support System for Breast Cancer Patients

    NASA Astrophysics Data System (ADS)

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

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

  7. Details of a Successful Clinical Decision Support System

    PubMed Central

    Friedlin, Jeff; Dexter, Paul R.; Overhage, J. Marc

    2007-01-01

    Computerized physician order entry (CPOE) with clinical decision support (CDS) is regarded as one of the most effective ways to improve the quality of health care and increase patient safety. As electronic medical records become more available, such systems will increasingly become the method of choice to achieve these goals. Creating a CPOE/CDS system is a complex task, and some fail despite time consuming and expensive development. The CPOE system at the Regenstrief Institute incorporates sophisticated CDS and is one of the oldest and most successful in the U.S. Many years in development, it is currently used by hundreds of providers. Our well established, successful system can serve as a template or model for the future development of similar systems. We recently completed a full analysis of our CPOE/CDS system and present details of its structure, functionality and contents. PMID:18693837

  8. Importance of Decision Support Implementation in Emergency Department Vancomycin Dosing

    PubMed Central

    Faine, Brett; Mohr, Nicholas; Harland, Kari K.; Rolfes, Kathryn; Porter, Blake; Fuller, Brian M.

    2015-01-01

    Introduction The emergency department (ED) plays a critical role in the management of life-threatening infection. Prior data suggest that ED vancomycin dosing is frequently inappropriate. The objective is to assess the impact of an electronic medical record (EMR) intervention designed to improve vancomycin dosing accuracy, on vancomycin dosing and clinical outcomes in critically ill ED patients. Methods Retrospective before-after cohort study of all patients (n=278) treated with vancomycin in a 60,000-visit Midwestern academic ED (March 2008 and April 2011) and admitted to an intensive care unit. The primary outcome was the proportion of vancomycin doses defined as “appropriate” based on recorded actual body weight. We also evaluated secondary outcomes of mortality and length of stay. Results The EMR dose calculation tool was associated with an increase in mean vancomycin dose ([14.1±5.0] vs. [16.5±5.7] mg/kg, p<0.001) and a 10.3% absolute improvement in first-dose appropriateness (34.3% vs. 24.0%, p=0.07). After controlling for age, gender, methicillin-resistant staphylococcus aureus infection, and Acute Physiology and Chronic Health Evaluation II score, 28-day in-hospital mortality (odds ratio OR 1.72; 95% CI [0.76–3.88], p=0.12) was not affected. Conclusion A computerized decision-support tool is associated with an increase in mean vancomycin dose in critically ill ED patients, but not with a statistically significant increase in therapeutic vancomycin doses. The impact of decision-support tools should be further explored to optimize compliance with accepted antibiotic guidelines and to potentially affect clinical outcome. PMID:26265968

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

    NASA Astrophysics Data System (ADS)

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

    2008-05-01

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

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

    PubMed Central

    2012-01-01

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

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

    PubMed

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Pulwarty, R. S.

    2012-12-01

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

  13. An architecture for rule based system explanation

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  14. Improvements in agricultural water decision support using remote sensing

    NASA Astrophysics Data System (ADS)

    Marshall, M. T.

    2012-12-01

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

  15. WEB-GIS Decision Support System for CO2 storage

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    SciTech Connect

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

    2000-06-01

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

  17. Decision support tools for environmentally safe use of pesticides.

    PubMed

    Doruchowski, G; Balsari, P; Marucco, P; Herbst, A; Wehmann, H-J; Roettele, M; Gil, E; Codis, S; Pauwelyn, E

    2013-01-01

    Prevention of environmental risk due to pesticide application is demanded by EU legislation regarding water and crop protection issues. The pesticide users are required to take responsibility for the environmental consequences of applications. Therefore they need to make responsible decisions at both strategic and tactical level. The first one is a long term decision on selection of equipment, and the other applies to decisions on use of equipment in actual meteorological and environmental situation at any time when treatment is needed. In order to assist the user to make proper decisions the decision support tools were developed in form of web-based applications: EOS - Environmentally Optimised Sprayer; DET--Drift Evaluation Tool. EOS performs evaluation of the sprayer in terms of its risk mitigation potential based on the technical solutions present on the sprayer and selected by the user. EOS has been designed as a stepwise structured questionnaire, divided in sections representing different sources of pollution, i.e. RISK AREAS (step 1): Inside contamination; outside contamination; Filling; Spray Loss (Drift); Remnants. Within each RISK AREA there were identified PROBLEMS (step 2) to be solved by different TECHNOLOGIES (step 3), evaluated in different ASPECTS (step 4) when the user selects TECHNICAL SOLUTION (step 5) used on the sprayer. The items of steps 1-4 were assigned weights (%) and the items of TECHNICAL SOLUTIONs were scored from 0 to 10 (10 = best in class). This stepwise approach and valuation of items allows for calculating the effective score of each individual TECHNICAL SOLUTION in terms of its risk mitigation potential. The sum of these individual scores related to the final score of environmentally optimised sprayer gives the evaluated sprayer's EOS index (%) expressing the environmental value of the sprayer. DET performs evaluation of drift risk in actual situation, and proposes measures to mitigate this risk, helping the operator to make

  18. Adriatic Sea Decision Support System (ADRI-DSS)

    NASA Astrophysics Data System (ADS)

    Coppini, Giovanni; Lyubartsev, Vladyslav; Pinardi, Nadia; Montanari, Giuseppe; Rinaldi, Attilio; Serra, Stefano; Santoleri, Rosalia

    2010-05-01

    The Adriatic Sea decision support system (ADRI-DSS) consists of an on-line service built upon a set of integrated operational oceanography products. ADRI-DSS integrates the Adriatic Sea monitoring and forecasting system (AFS) with local in-situ observations and is built to support the Emilia-Romagna coastal monitoring system for marine environment and ecosystem health. The target user is the Regional Environment Prevention Agency from Emilia-Romagna (Italy) called ARPA-EMR. Specifically ADRI-DSS will support the daily action of the oceanographic section of ARPA-EMR called ARPA-DAPHNE providing all the available products (forecast, observations, simulations) from Adriatic Forecasting System. The product is shaped as required by the user and moreover ADRI-DSS also integrates with the routinely observations that the user carry out on a weekly basis. The system has been designed through the interaction with ARPA-DAPHNE and consists of a online portal containing simulation and forecast for the relevant north Adriatic region. Moreover the model products are compared with in-situ observations of temperature and salinity collected by the ARPA-DAPHNE itself. In the coming future also satellite observations and indicators will be made available by ADRI-DSS. The final aim of ADRI-DSS is to integrate selected products from the AFS with the insitu and satellite observation to support the monitoring activities of ARPA-DAPNHE and to improve ARPA-DAPHNE capabilities for the Emilia-Romagna marine environment status assessment. ADRI-DSS has been developed within ECOOP project (European COastal-shelf sea OPerational Observing and forecasting system Integrated Project). ADRI-DSS is a web-based application available via internet browsers with JavaScript capability. The server part is implemented on PHP (data management) and NCL (graphics production). The NCL is NCAR Command Language, a free interpreted language designed specifically for scientific data processing and visualization, see

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

    NASA Technical Reports Server (NTRS)

    McKellipo, Rodney; Ross, Kenton W.

    2006-01-01

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

  20. Decision support system for managing oil spill events.

    PubMed

    Keramitsoglou, Iphigenia; Cartalis, Constantinos; Kassomenos, Pavlos

    2003-08-01

    The Mediterranean environment is exposed to various hazards, including oil spills, forest fires, and floods, making the development of a decision support system (DSS) for emergency management an objective of utmost importance. The present work presents a complete DSS for managing marine pollution events caused by oil spills. The system provides all the necessary tools for early detection of oil-spills from satellite images, monitoring of their evolution, estimation of the accident consequences and provision of support to responsible Public Authorities during clean-up operations. The heart of the system is an image processing-geographic information system and other assistant individual software tools that perform oil spill evolution simulation and all other necessary numerical calculations as well as cartographic and reporting tasks related to a specific management of the oil spill event. The cartographic information is derived from the extant general maps representing detailed information concerning several regional environmental and land-cover characteristics as well as financial activities of the application area. Early notification of the authorities with up-to-date accurate information on the position and evolution of the oil spill, combined with the detailed coastal maps, is of paramount importance for emergency assessment and effective clean-up operations that would prevent environmental hazard. An application was developed for the Region of Crete, an area particularly vulnerable to oil spills due to its location, ecological characteristics, and local economic activities. PMID:14753653

  1. The Aegean Sea marine security decision support system

    NASA Astrophysics Data System (ADS)

    Perivoliotis, L.; Krokos, G.; Nittis, K.; Korres, G.

    2011-05-01

    As part of the integrated ECOOP (European Coastal Sea Operational observing and Forecasting System) project, HCMR upgraded the already existing standalone Oil Spill Forecasting System for the Aegean Sea, initially developed for the Greek Operational Oceanography System (POSEIDON), into an active element of the European Decision Support System (EuroDeSS). The system is accessible through a user friendly web interface where the case scenarios can be fed into the oil spill drift model component, while the synthetic output contains detailed information about the distribution of oil spill particles and the oil spill budget and it is provided both in text based ECOOP common output format and as a series of sequential graphics. The main development steps that were necessary for this transition were the modification of the forcing input data module in order to allow the import of other system products which are usually provided in standard formats such as NetCDF and the transformation of the model's calculation routines to allow use of current, density and diffusivities data in z instead of sigma coordinates. During the implementation of the Aegean DeSS, the system was used in operational mode in order support the Greek marine authorities in handling a real accident that took place in North Aegean area. Furthermore, the introduction of common input and output files by all the partners of EuroDeSS extended the system's interoperability thus facilitating data exchanges and comparison experiments.

  2. The Aegean sea marine security decision support system

    NASA Astrophysics Data System (ADS)

    Perivoliotis, L.; Krokos, G.; Nittis, K.; Korres, G.

    2011-10-01

    As part of the integrated ECOOP (European Coastal Sea Operational observing and Forecasting System) project, HCMR upgraded the already existing standalone Oil Spill Forecasting System for the Aegean Sea, initially developed for the Greek Operational Oceanography System (POSEIDON), into an active element of the European Decision Support System (EuroDeSS). The system is accessible through a user friendly web interface where the case scenarios can be fed into the oil spill drift model component, while the synthetic output contains detailed information about the distribution of oil spill particles and the oil spill budget and it is provided both in text based ECOOP common output format and as a series of sequential graphics. The main development steps that were necessary for this transition were the modification of the forcing input data module in order to allow the import of other system products which are usually provided in standard formats such as NetCDF and the transformation of the model's calculation routines to allow use of current, density and diffusivities data in z instead of sigma coordinates. During the implementation of the Aegean DeSS, the system was used in operational mode in order to support the Greek marine authorities in handling a real accident that took place in North Aegean area. Furthermore, the introduction of common input and output files by all the partners of EuroDeSS extended the system's interoperability thus facilitating data exchanges and comparison experiments.

  3. Reducing inappropriate ESR testing with computerized clinical decision support

    PubMed Central

    Gottheil, Stephanie; Khemani, Ekta; Copley, Katherine; Keeney, Michael; Kinney, Jeff; Chin-Yee, Ian; Gob, Alan

    2016-01-01

    Laboratory test overutilization increases health care costs, leads to unwarranted investigations, and may have a negative impact on health outcomes. The American Society of Clinical Pathology, in its Choosing Wisely Campaign, advocates that inflammation be investigated with C-reactive protein (CRP) instead of Erythrocyte Sedimentation Rate (ESR). London Health Sciences Centre (LHSC), a tertiary care hospital organization in Ontario, Canada, set a goal to reduce inappropriate ESR orders by 50%. After developing appropriateness criteria for ESR, we used a series of PDSA cycles to reduce inappropriate ESR ordering and analyzed our results with an interrupted time series design. Our intervention began with an educational bulletin and moved to city-wide implementation of computerized Clinical Decision Support (CDS). After implementation, ESR orders decreased by 40% from 386 orders per week to 241 orders per week. Our results are supported by previous literature on the effectiveness of CDS in reducing overutilization and suggest that provider habit is a significant contributor to inappropriate ordering. PMID:27096092

  4. Reducing inappropriate ESR testing with computerized clinical decision support.

    PubMed

    Gottheil, Stephanie; Khemani, Ekta; Copley, Katherine; Keeney, Michael; Kinney, Jeff; Chin-Yee, Ian; Gob, Alan

    2016-01-01

    Laboratory test overutilization increases health care costs, leads to unwarranted investigations, and may have a negative impact on health outcomes. The American Society of Clinical Pathology, in its Choosing Wisely Campaign, advocates that inflammation be investigated with C-reactive protein (CRP) instead of Erythrocyte Sedimentation Rate (ESR). London Health Sciences Centre (LHSC), a tertiary care hospital organization in Ontario, Canada, set a goal to reduce inappropriate ESR orders by 50%. After developing appropriateness criteria for ESR, we used a series of PDSA cycles to reduce inappropriate ESR ordering and analyzed our results with an interrupted time series design. Our intervention began with an educational bulletin and moved to city-wide implementation of computerized Clinical Decision Support (CDS). After implementation, ESR orders decreased by 40% from 386 orders per week to 241 orders per week. Our results are supported by previous literature on the effectiveness of CDS in reducing overutilization and suggest that provider habit is a significant contributor to inappropriate ordering. PMID:27096092

  5. Creating a GIS-Based Decision-Support System

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  6. Evaluating clinical decision support rules as an intervention in clinician workflows with technology.

    PubMed

    Brokel, Jane M; Schwichtenberg, Tamara J; Wakefield, Douglas S; Ward, Marcia M; Shaw, Michael G; Kramer, J Michael

    2011-01-01

    The implementation of electronic health records in rural settings generated new challenges beyond those seen in urban hospitals. The preparation, implementation, and sustaining of clinical decision support rules require extensive attention to standards, content design, support resources, expert knowledge, and more. A formative evaluation was used to present progress and evolution of clinical decision support rule implementation and use within clinician workflows for application in an electronic health record. The rural hospital was able to use clinical decision support rules from five urban hospitals within its system to promote safety, prevent errors, establish evidence-based practices, and support communication. This article describes tools to validate initial 54 clinical decision support rules used in a rural referral hospital and 17 used in clinics. Since 2005, the study hospital has added specific system clinical decision support rules for catheter-acquired urinary tract infection, deep venous thrombosis, heart failure, and more. The findings validate the use of clinical decision support rules across sites and ability to use existing indicators to measure outcomes. Rural hospitals can rapidly overcome the barriers to prepare and implement as well as sustain use of clinical decision support rules with a systemized approach and support structures. A model for design and validation of clinical decision support rules into workflow processes is presented. The replication and reuse of clinical decision support rule templates with data specifications that follow data models can support reapplication of the rule intervention in subsequent rural and critical access hospitals through system support resources. PMID:21099543

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

    SciTech Connect

    Brothers, A.J.

    1995-12-31

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

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Huo, Hanqiang

    2010-07-01

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

  10. A Rule-Based Industrial Boiler Selection System

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    ERIC Educational Resources Information Center

    Chaffee, Ellen Earle

    1982-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  13. Decision support system for breast cancer detection using mammograms.

    PubMed

    Ganesan, Karthikeyan; Acharya, Rajendra U; Chua, Chua K; Min, Lim C; Mathew, Betty; Thomas, Abraham K

    2013-07-01

    Mammograms are by far one of the most preferred methods of screening for breast cancer. Early detection of breast cancer can improve survival rates to a greater extent. Although the analysis and diagnosis of breast cancer are done by experienced radiologists, there is always the possibility of human error. Interobserver and intraobserver errors occur frequently in the analysis of medical images, given the high variability between every patient. Also, the sensitivity of mammographic screening varies with image quality and expertise of the radiologist. So, there is no golden standard for the screening process. To offset this variability and to standardize the diagnostic procedures, efforts are being made to develop automated techniques for diagnosis and grading of breast cancer images. This article presents a classification pipeline to improve the accuracy of differentiation between normal, benign, and malignant mammograms. Several features based on higher-order spectra, local binary pattern, Laws' texture energy, and discrete wavelet transform were extracted from mammograms. Feature selection techniques based on sequential forward, backward, plus-l-takeaway-r, individual, and branch-and-bound selections using the Mahalanobis distance criterion were used to rank the features and find classification accuracies for combination of several features based on the ranking. Six classifiers were used, namely, decision tree classifier, fisher classifier, linear discriminant classifier, nearest mean classifier, Parzen classifier, and support vector machine classifier. We evaluated our proposed methodology with 300 mammograms obtained from the Digital Database for Screening Mammography and 300 mammograms from the Singapore Anti-Tuberculosis Association CommHealth database. Sensitivity, specificity, and accuracy values were used to compare the performances of the classifiers. Our results show that the decision tree classifier demonstrated an excellent performance compared to

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  15. Virtual support for paediatric HIV treatment decision making

    PubMed Central

    Le Doare, Kirsty; Mackie, N E; Kaye, S; Bamford, A; Walters, S; Foster, C

    2015-01-01

    Objective The objective of this study is to review clinical outcomes of recommendations made by a multidisciplinary paediatric virtual clinic (PVC) for complex case management of paediatric HIV as a model of care within a tertiary network. Design A retrospective review of the clinical outcomes of paediatric and adolescent (0–21 years) referrals to the PVC at St. Mary's Hospital, Imperial College Healthcare NHS Trust, London was performed between October 2009 and November 2013. Results 234 referrals were made for 182 children from 37 centres, discussed in 42 meetings (median age 13 years, IQR 10–15 years). Reasons for referral included virological failure (44%), simplification of the current regimen (24%) and antiretroviral drug complications (24%). At latest follow-up, PVC advice had been instituted in 80% of referrals. Suppression following virological failure was achieved in 48% following first referral and 57% following subsequent discussions and was maintained in 95% of children referred for regimen simplification. Following advice, dyslipidaemia resolved in 42% and liver function normalised in 73% with biochemical hepatitis. Adherence support aided resolution of viraemia in nine children and 12% of referrals resulted in additional support, including psychology, social services and mental health input. Conclusions Combined multidisciplinary virtual input with adult expertise in resistance and newer agents, paediatric knowledge of pill swallowing, childhood formulations/weight banding and parental support, assists complex treatment decision making in paediatric HIV infection. The Virtual Clinic model could be applied to the management of other rare complex diseases of childhood within a clinical network. PMID:25549664

  16. Applications of fuzzy sets to rule-based expert system development

    NASA Technical Reports Server (NTRS)

    Lea, Robert N.

    1989-01-01

    Problems of implementing rule-based expert systems using fuzzy sets are considered. A fuzzy logic software development shell is used that allows inclusion of both crisp and fuzzy rules in decision making and process control problems. Results are given that compare this type of expert system to a human expert in some specific applications. Advantages and disadvantages of such systems are discussed.

  17. Rule-based expert system for maritime anomaly detection

    NASA Astrophysics Data System (ADS)

    Roy, Jean

    2010-04-01

    Maritime domain operators/analysts have a mandate to be aware of all that is happening within their areas of responsibility. This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc., and it has become more challenging in the past decade, as commercial shipping turned into a potential threat. In particular, a huge portion of the data and information made available to the operators/analysts is mundane, from maritime platforms going about normal, legitimate activities, and it is very challenging for them to detect and identify the non-mundane. To achieve such anomaly detection, they must establish numerous relevant situational facts from a variety of sensor data streams. Unfortunately, many of the facts of interest just cannot be observed; the operators/analysts thus use their knowledge of the maritime domain and their reasoning faculties to infer these facts. As they are often overwhelmed by the large amount of data and information, automated reasoning tools could be used to support them by inferring the necessary facts, ultimately providing indications and warning on a small number of anomalous events worthy of their attention. Along this line of thought, this paper describes a proof-of-concept prototype of a rule-based expert system implementing automated rule-based reasoning in support of maritime anomaly detection.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  19. Simulation of large-scale rule-based models

    SciTech Connect

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

    2008-01-01

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

  20. Hypoplastic left heart syndrome: parent support for early decision making.

    PubMed

    Toebbe, Sarah; Yehle, Karen; Kirkpatrick, Jane; Coddington, Jennifer

    2013-01-01

    Hypoplastic left heart syndrome is a life threatening congenital cardiac anomaly. After a child has been diagnosed with hypoplastic left heart syndrome, parents must make life or death decisions within days of birth. Healthcare providers must provide appropriate education so that parents are able to make informed, timely decisions. Information regarding the diagnosis, treatment options, and parental decision making process for initial decision making for hypoplastic left heart syndrome are provided to guide nurses who work with these families. The challenging decision making process that parents must go through after diagnosis of hypoplastic left heart syndrome will be described. PMID:23246301

  1. Towards a Decision Support System for Space Flight Operations

    NASA Technical Reports Server (NTRS)

    Meshkat, Leila; Hogle, Charles; Ruszkowski, James

    2013-01-01

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

  2. Visualization Component of Vehicle Health Decision Support System

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

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

    ERIC Educational Resources Information Center

    Petrides, Lisa A.; McClelland, Sara I.

    2007-01-01

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

  4. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: JOURNAL ARTICLE

    EPA Science Inventory

    NRMRL-CIN-1351 Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. Risk Analysis 600/R/01/104, Available: on internet, www.epa.gov/ORD/NRMRL/Pubs/600R01104, [NET]. 03/07/2001 D...

  5. Generalized Tumor Dose for Treatment Planning Decision Support

    NASA Astrophysics Data System (ADS)

    Zuniga, Areli A.

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

  6. Decision aid tools to support women's decision making in pregnancy and birth: a systematic review and meta-analysis.

    PubMed

    Dugas, Marylène; Shorten, Allison; Dubé, Eric; Wassef, Maggy; Bujold, Emmanuel; Chaillet, Nils

    2012-06-01

    Support for a model of shared medical decision making, where women and their care providers discuss risks and benefits of their different options, reveal their preferences, and jointly make a decision, is a growing expectation in obstetric care. The objective of this study was to conduct a systematic review and meta-analysis of randomized controlled trials evaluating the efficacy of different decision aid tools compared to regular care for women facing several options in the specific field of obstetric care. We included published studies about interventions designed to aid mothers' decision making and provide information about obstetrical treatment or screening options. Following a search of electronic databases for articles published in English and French from 1994 to 2010, we found ten studies that met the inclusion criteria. In this systematic review and meta-analysis we found that all decision aid tools, except for Decision Trees, facilitated significant increases in knowledge. The Computer-based Information Tool, the Decision Analysis Tools, Individual Counseling and Group Counseling intervention presented significant results in reducing anxiety levels. The Decision Analysis Tools and the Computer-based Information tool were associated with a reduction in levels of decisional conflict. The Decision Analysis Tool was the only tool that presented evidence of an impact on the final choice and final outcome. Decision aid tools can assist health professionals to provide information and counseling about choices during pregnancy and support women in shared decision making. The choice of a specific tool should depend on resources available to support their use as well as the specific decisions being faced by women, their health care setting and providers. PMID:22475401

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

    PubMed

    Forgionne, G A

    1991-01-01

    The paper reports a decision support system (DSS) that enables health plan administrators to quickly and easily: (1) manage relevant medical care market (consumer preference and competitors' program) information and (2) convert the information into appropriate medical care delivery and/or payment policies. As the paper demonstrates, the DSS enables providers to design cost efficient and market effective medical care programs. The DSS provides knowledge about subscriber preferences, customer desires, and the program offerings of the competition. It then helps administrators structure a medical care plan in a way that best meets consumer needs in view of the competition. This market effective plan has the potential to generate substantial amounts of additional revenue for the program. Since the system's data base consists mainly of the provider's records, routine transactions, and other readily available documents, the DSS can be implemented at a nominal incremental cost. The paper also evaluates the impact of the information system on the general financial performance of existing dental and mental health plans. In addition, the paper examines how the system can help contain the cost of providing medical care while providing better services to more potential beneficiaries than current approaches. PMID:10111964

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

    PubMed

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

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

  9. Decision support system for the provision of emergency sanitation.

    PubMed

    Zakaria, F; Garcia, H A; Hooijmans, C M; Brdjanovic, D

    2015-04-15

    Proper provision of sanitation in emergencies is considered a life-saving intervention. Without access to sanitation, refugees at emergency camps are at a high risk of contracting diseases. Even the most knowledgeable relief agencies have experienced difficulties providing sanitation alternatives in such challenging scenarios. This study developed a computer-based decision support system (DSS) to plan a sanitation response in emergencies. The sanitation alternatives suggested by the DSS are based on a sanitation chain concept that considers different steps in the faecal sludge management, from the toilet or latrine to the safe disposal of faecal matters. The DSS first screens individual sanitation technologies using the user's given input. Remaining sanitation options are then built into a feasible sanitation chain. Subsequently, each technology in the chain is evaluated on a scoring system. Different sanitation chains can later be ranked based on the total evaluation scores. The DSS addresses several deficiencies encountered in the provision of sanitation in emergencies including: the application of standard practices and intuition, the omission of site specific conditions, the limited knowledge exhibited by emergency planners, and the provision of sanitation focused exclusively on the collection step (i.e., just the provision of toilets). PMID:25662862

  10. Agricultural Model for the Nile Basin Decision Support System

    NASA Astrophysics Data System (ADS)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

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

  11. Clinical Decision Support for Early Recognition of Sepsis

    PubMed Central

    Amland, Robert C.; Hahn-Cover, Kristin E.

    2014-01-01

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

  12. A Semantic Sensor Web for Environmental Decision Support Applications

    PubMed Central

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

    2011-01-01

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

  13. Type-II Fuzzy Decision Support System for Fertilizer

    PubMed Central

    Ashraf, Ather; Sarwar, Mansoor

    2014-01-01

    Type-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or range of classes. But there exists an uncertainty about the shape of the membership, that is, whether to go for a triangle membership function or a trapezoidal membership function. In this paper we use a type-II fuzzy set to overcome this uncertainty, and develop a fuzzy decision support system of fertilizers based on a type-II fuzzy set. This type-II fuzzy system takes cropping time and soil nutrients in the form of spatial surfaces as input, fuzzifies it using a type-II fuzzy membership function, and implies fuzzy rules on it in the fuzzy inference engine. The output of the fuzzy inference engine, which is in the form of interval value type-II fuzzy sets, reduced to an interval type-I fuzzy set, defuzzifies it to a crisp value and generates a spatial surface of fertilizers. This spatial surface shows the spatial trend of the required amount of fertilizer needed to cultivate a specific crop. The complexity of our algorithm is O(mnr), where m is the height of the raster, n is the width of the raster, and r is the number of expert rules. PMID:24892071

  14. Prognostic decision support using symbolic dynamics in CTG monitoring.

    PubMed

    Cesarelli, Mario; Romano, Maria; Bifulco, Paolo; Improta, Giovanni; D'Addio, Giovanni

    2013-01-01

    Foetal heart rate variability is one of the most important parameters to monitor foetal wellbeing. Linear parameters, widely employed to study foetal heart variability, have shown some limitations in highlight dynamics potentially relevant. During the last decades, therefore, nonlinear analysis methods have gained a growing interest to analyze the chaotic nature of cardiac activity. Parameters derived by techniques investigating nonlinear can be included in computerised systems of cardiotocographic monitoring. In this work, we described an application of symbolic dynamics to analyze foetal heart rate variability in healthy foetuses and a concise index, introduced for its classification in antepartum CTG monitoring. The introduced index demonstrated to be capable to highlight differences in heart rate variability and resulted correlated with the Apgar score at birth, in particular, higher variability indexes values are associated to early greater vitality at birth. These preliminary results confirm that SD can be a helpful tool in CTG monitoring, supporting medical decisions in order to assure the maximum well-being of newborns. PMID:23542985

  15. Geospatial decision support framework for critical infrastructure interdependency assessment

    NASA Astrophysics Data System (ADS)

    Shih, Chung Yan

    Critical infrastructures, such as telecommunications, energy, banking and finance, transportation, water systems and emergency services are the foundations of modern society. There is a heavy dependence on critical infrastructures at multiple levels within the supply chain of any good or service. Any disruptions in the supply chain may cause profound cascading effect to other critical infrastructures. A 1997 report by the President's Commission on Critical Infrastructure Protection states that a serious interruption in freight rail service would bring the coal mining industry to a halt within approximately two weeks and the availability of electric power could be reduced in a matter of one to two months. Therefore, this research aimed at representing and assessing the interdependencies between coal supply, transportation and energy production. A proposed geospatial decision support framework was established and applied to analyze interdependency related disruption impact. By utilizing the data warehousing approach, geospatial and non-geospatial data were retrieved, integrated and analyzed based on the transportation model and geospatial disruption analysis developed in the research. The results showed that by utilizing this framework, disruption impacts can be estimated at various levels (e.g., power plant, county, state, etc.) for preventative or emergency response efforts. The information derived from the framework can be used for data mining analysis (e.g., assessing transportation mode usages; finding alternative coal suppliers, etc.).

  16. Computer aided decision support system for cervical cancer classification

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    EPA Science Inventory

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

  19. Health innovations in patient decision support: Bridging the gaps and challenges.

    PubMed

    Ng, Chirk Jenn; Lee, Yew Kong; Lee, Ping Yein; Abdullah, Khatijah Lim

    2013-01-01

    Patient decision aids (PDAs) help to support patients in making an informed and value-based decision. Despite advancement in decision support technologies over the past 30 years, most PDAs are still inaccessible and few address individual needs. Health innovation may provide a solution to bridge these gaps. Information and computer technology provide a platform to incorporate individual profiles and needs into PDAs, making the decision support more personalised. Health innovation may enhance accessibility by using mobile, tablet and Internet technologies; make risk communication more interactive; and identify patient values more effectively. In addition, using databases to capture patient data and the usage of PDAs can help: developers to improve PDAs' design; clinicians to facilitate the decisionmaking process more effectively; and policy makers to make shared decision making more feasible and cost-effective. Health innovation may hold the key to advancing PDAs by creating a more personalised and effective decision support tool for patients making healthcare decisions. PMID:23483776

  20. An Oceanographic Decision Support System for Scientific Field Experiments

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  1. SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

    PubMed

    Wright, Adam; Sittig, Dean F

    2008-12-01

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

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

    PubMed

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

    2007-09-01

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

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

    PubMed Central

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

    2013-01-01

    Patients in the intensive care unit (ICU) who require mechanical ventilation due to acute respiratory failure also frequently require the administration of sedative agents. The need for sedation arises both from patient anxiety due to the loss of personal control and the unfamiliar and intrusive environment of the ICU, and also due to pain or other variants of noxious stimuli. While physicians select the agent(s) used for sedation and cardiovascular function, the actual administration of these agents is the responsibility of the nursing staff. If clinical decision support systems and closed-loop control systems could be developed for critical care monitoring and lifesaving interventions as well as the administration of sedation and cardiopulmonary management, the ICU nurse could be released from the intense monitoring of sedation, allowing her/him to focus on other critical tasks. One particularly attractive strategy is to utilize the knowledge and experience of skilled clinicians, capturing explicitly the rules expert clinicians use to decide on how to titrate drug doses depending on the level of sedation. In this paper, we extend the deterministic rule-based expert system for cardiopulmonary management and ICU sedation framework presented in [1] to a stochastic setting by using probability theory to quantify uncertainty and hence deal with more realistic clinical situations. PMID:23620646

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

    PubMed

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

    2012-03-01

    Patients in the intensive care unit (ICU) who require mechanical ventilation due to acute respiratory failure also frequently require the administration of sedative agents. The need for sedation arises both from patient anxiety due to the loss of personal control and the unfamiliar and intrusive environment of the ICU, and also due to pain or other variants of noxious stimuli. While physicians select the agent(s) used for sedation and cardiovascular function, the actual administration of these agents is the responsibility of the nursing staff. If clinical decision support systems and closed-loop control systems could be developed for critical care monitoring and lifesaving interventions as well as the administration of sedation and cardiopulmonary management, the ICU nurse could be released from the intense monitoring of sedation, allowing her/him to focus on other critical tasks. One particularly attractive strategy is to utilize the knowledge and experience of skilled clinicians, capturing explicitly the rules expert clinicians use to decide on how to titrate drug doses depending on the level of sedation. In this paper, we extend the deterministic rule-based expert system for cardiopulmonary management and ICU sedation framework presented in [1] to a stochastic setting by using probability theory to quantify uncertainty and hence deal with more realistic clinical situations. PMID:23620646

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  6. Implementation and Testing of Interdisciplinary Decision Support Tools to Standardize Discharge Planning

    PubMed Central

    Bowles, Kathryn H.; Holland, Diane E.; Potashnik, Sheryl L.

    2012-01-01

    Improving transitions in care is an international priority. In acute care, this complex process starts upon admission and requires multiple interventions to appropriately transition patients from one setting to the next. Within this multi-step process are two important decision points that warrant standardization and support. Our research teams have developed decision support tools that meet this critical need. The Early Screen for Discharge Planning (ESDP) and the Discharge Decision Support System (D2S2) bring evidence based, interdisciplinary decision support to two common and important decisions. The purpose of this paper is to share information about “real life” experiences in implementing decision support covering the development and use of the tools, advising about implementation considerations, making suggestions for automating the process, and sharing findings from our recent implementation study. PMID:24199045

  7. PARAMETERIZING GPFARM: AN AGRICULTURAL DECISION SUPPORT SYSTEM FOR INTEGRATING SCIENCE, ECONOMICS, RESOURCE USE, AND ENVIRONMENTAL IMPACTS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Few farmers and ranchers adopt agricultural software such as decision support systems (DSS). While numerous decision aids are available, most are too difficult for producers to use, exclude components (e.g., economic budgeting, weeds, multicriteria decision analysis) necessary for meaningful use on...

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

    ERIC Educational Resources Information Center

    Hartley, Roger; Almuhaidib, Saud M. Y.

    2007-01-01

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

  9. Representation requirements for supporting knowledge-based construction of decision models in medicine.

    PubMed Central

    Leong, T. Y.

    1991-01-01

    This paper analyzes the medical knowledge required for formulating decision models in the domain of pulmonary infectious diseases (PIDs) with acquired immunodeficiency syndrome (AIDS). Aiming to support dynamic decision-modeling, the knowledge characterization focuses on the ontology of the clinical decision problem. Relevant inference patterns and knowledge types are identified. PMID:1807680

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

    EPA Science Inventory

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

  11. A rule-based software test data generator

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  12. A High-Level Language for Rule-Based Modelling

    PubMed Central

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

    2015-01-01

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

  13. Approaches to the verification of rule-based expert systems

    NASA Technical Reports Server (NTRS)

    Culbert, Chris; Riley, Gary; Savely, Robert T.

    1987-01-01

    Expert systems are a highly useful spinoff of artificial intelligence research. One major stumbling block to extended use of expert systems is the lack of well-defined verification and validation (V and V) methodologies. Since expert systems are computer programs, the definitions of verification and validation from conventional software are applicable. The primary difficulty with expert systems is the use of development methodologies which do not support effective V and V. If proper techniques are used to document requirements, V and V of rule-based expert systems is possible, and may be easier than with conventional code. For NASA applications, the flight technique panels used in previous programs should provide an excellent way to verify the rules used in expert systems. There are, however, some inherent differences in expert systems that will affect V and V considerations.

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

    PubMed

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

    2015-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    EPA Science Inventory

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    EPA Science Inventory

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

  1. Developing a Microcomputer-Based Decision Support System: People and Process.

    ERIC Educational Resources Information Center

    Starratt, Joseph; And Others

    1990-01-01

    Discusses the need for management information and decision support systems in libraries, and identifies inertia and confusion as the main contributors to the lack of successful implementations. An attempt to initiate a decision support system at the University of Nebraska at Omaha is described, and both problems encountered and benefits gained are…

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    ERIC Educational Resources Information Center

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

    2013-01-01

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

  4. Using real options analysis to support strategic management decisions

    NASA Astrophysics Data System (ADS)

    Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

    2013-12-01

    Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

  5. A graphical, rule based robotic interface system

    NASA Technical Reports Server (NTRS)

    Mckee, James W.; Wolfsberger, John

    1988-01-01

    The ability of a human to take control of a robotic system is essential in any use of robots in space in order to handle unforeseen changes in the robot's work environment or scheduled tasks. But in cases in which the work environment is known, a human controlling a robot's every move by remote control is both time consuming and frustrating. A system is needed in which the user can give the robotic system commands to perform tasks but need not tell the system how. To be useful, this system should be able to plan and perform the tasks faster than a telerobotic system. The interface between the user and the robot system must be natural and meaningful to the user. A high level user interface program under development at the University of Alabama, Huntsville, is described. A graphical interface is proposed in which the user selects objects to be manipulated by selecting representations of the object on projections of a 3-D model of the work environment. The user may move in the work environment by changing the viewpoint of the projections. The interface uses a rule based program to transform user selection of items on a graphics display of the robot's work environment into commands for the robot. The program first determines if the desired task is possible given the abilities of the robot and any constraints on the object. If the task is possible, the program determines what movements the robot needs to make to perform the task. The movements are transformed into commands for the robot. The information defining the robot, the work environment, and how objects may be moved is stored in a set of data bases accessible to the program and displayable to the user.

  6. Mountaineer`s gas facilities decision support system

    SciTech Connect

    1997-02-01

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

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

    PubMed

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

    2009-04-01

    Domains such as force protection require an effective decision maker to maintain a high level of situation awareness. A system that combines humans with neural networks is a desirable approach. Furthermore, it is advantageous for the calculation engine to operate in three learning modes: supervised for initial training and known updating, reinforcement for online operational improvement, and unsupervised in the absence of all external signaling. An Adaptive Resonance Theory based architecture capable of seamlessly switching among the three types of learning is discussed that can be used to help optimize the decision making of a human operator in such a scenario. This is followed by a situation assessment module. PMID:19395234

  8. IMPROVED SCIENCE AND DECISION SUPPORT FOR MANAGING WATERSHED NUTRIENT LOADS

    EPA Science Inventory

    The proposed research addresses two critical gaps in the TMDL process: (1) the inadequacy of presently existing receiving water models to accurately simulate nutrient-sediment-water interactions and fixed plants; and (2) the lack of decision-oriented optimization f...

  9. Improving Information Products for System 2 Decision Support

    ERIC Educational Resources Information Center

    Gibson, Neal

    2010-01-01

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

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

    ERIC Educational Resources Information Center

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

    2004-01-01

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

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

    EPA Science Inventory

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

  12. Hydrologic Drought Decision Support System (HyDroDSS)

    USGS Publications Warehouse

    Granato, Gregory E.

    2014-01-01

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

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

    PubMed Central

    2011-01-01

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

  14. Interventions to support children’s engagement in health-related decisions: a systematic review

    PubMed Central

    2014-01-01

    Background Children often need support in health decision-making. The objective of this study was to review characteristics and effectiveness of interventions that support health decision-making of children. Methods A systematic review. Electronic databases (PubMed, the Cochrane Library, Web of Science, Scopus, ProQuest Dissertations and Theses, CINAHL, PsycINFO, MEDLINE, and EMBASE) were searched from inception until March 2012. Two independent reviewers screened eligibility: a) intervention studies; b) involved supporting children (≤18 years) considering health-related decision(s); and c) measured decision quality or decision-making process outcomes. Data extraction and quality appraisal were conducted by one author and verified by another using a standardized data extraction form. Quality appraisal was based on the Cochrane Risk of Bias tool. Results Of 4313 citations, 5 studies were eligible. Interventions focused on supporting decisions about risk behaviors (n = 3), psycho-educational services (n = 1), and end of life (n = 1). Two of 5 studies had statistically significant findings: i) compared to attention placebo, decision coaching alone increased values congruence between child and parent, and child satisfaction with decision-making process (lower risk of bias); ii) compared to no intervention, a workshop with weekly assignments increased overall decision-making quality (higher risk of bias). Conclusions Few studies have focused on interventions to support children’s participation in decisions about their health. More research is needed to determine effective methods for supporting children’s health decision-making. PMID:24758566

  15. A rule-based systems approach to spacecraft communications configuration optimization

    NASA Technical Reports Server (NTRS)

    Rash, James L.; Wong, Yen F.; Cieplak, James J.

    1988-01-01

    An experimental rule-based system for optimizing user spacecraft communications configurations was developed at NASA to support mission planning for spacecraft that obtain telecommunications services through NASA's Tracking and Data Relay Satellite System. Designated Expert for Communications Configuration Optimization (ECCO), and implemented in the OPS5 production system language, the system has shown the validity of a rule-based systems approach to this optimization problem. The development of ECCO and the incremental optimizatin method on which it is based are discussed. A test case using hypothetical mission data is included to demonstrate the optimization concept.

  16. A rule-based systems approach to spacecraft communications configuration optimization

    NASA Technical Reports Server (NTRS)

    Rash, James L.; Wong, Yen F.; Cieplak, James J.

    1988-01-01

    An experimental rule-based system for optimizing user spacecraft communications configurations was developed at NASA to support mission planning for spacecraft that obtain telecommunications services through NASA's Tracking and Data Relay Satellite System. Designated Expert for Communications Configuration Optimization (ECCO), and implemented in the OPS5 production system language, the system has shown the validity of a rule-based systems approach to this optimization problem. The development of ECCO and the incremental optimization method on which it is based are discussed. A test case using hypothetical mission data is included to demonstrate the optimization concept.

  17. A rule-based systems approach to spacecraft communications configuration optimization

    NASA Astrophysics Data System (ADS)

    Rash, James L.; Wong, Yen F.; Cieplak, James J.

    An experimental rule-based system for optimizing user spacecraft communications configurations was developed at NASA to support mission planning for spacecraft that obtain telecommunications services through NASA's Tracking and Data Relay Satellite System. Designated Expert for Communications Configuration Optimization (ECCO), and implemented in the OPS5 production system language, the system has shown the validity of a rule-based systems approach to this optimization problem. The development of ECCO and the incremental optimizatin method on which it is based are discussed. A test case using hypothetical mission data is included to demonstrate the optimization concept.

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

    SciTech Connect

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

    2013-05-15

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

  19. Supported decision making: the rights of people with dementia.

    PubMed

    Keeling, Amanda

    2016-03-23

    The Mental Capacity Act 2005 is used to assess a person's decision-making ability and to make a best interests decision where the individual lacks the capacity to do so. The act was considered to have the potential to maximise the autonomy of individuals with mental or cognitive impairments, but this has not been fully realised. Since the act came into force, the United Nations Convention on the Rights of Persons with Disabilities has challenged many of the principles underpinning the act. That challenge and how existing provisions in the act can be implemented to increase autonomy and control for people with cognitive or mental impairments are discussed. The principles of the convention are described and potential future amendments to the law are identified. PMID:27008152

  20. A Scalable Architecture for Rule Engine Based Clinical Decision Support Systems.

    PubMed

    Chattopadhyay, Soumi; Banerjee, Ansuman; Banerjee, Nilanjan

    2015-01-01

    Clinical Decision Support systems (CDSS) have reached a fair level of sophistication and have emerged as the popular system of choice for their aid in clinical decision making. These decision support systems are based on rule engines navigate through a repertoire of clinical rules and multitudes of facts to assist a clinical expert to decide on the set of actuations in response to a medical situation. In this paper, we present the design of a scalable architecture for a rule engine based clinical decision system. PMID:26262249

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

    PubMed Central

    Hutton, Guy

    2008-01-01

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

  2. Developing Climate Resilience Toolkit Decision Support Training Sectio

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed

    Liu, Xin; Wirtz, Kai W

    2006-06-30

    Studies on multi-group multi-criteria decision-making problems for oil spill contingency management are in their infancy. This paper presents a second-order fuzzy comprehensive evaluation (FCE) model to resolve decision-making problems in the area of contingency management after environmental disasters such as oil spills. To assess the performance of different oil combat strategies, second-order FCE allows for the utilization of lexical information, the consideration of ecological and socio-economic criteria and the involvement of a variety of stakeholders. On the other hand, the new approach can be validated by using internal and external checks, which refer to sensitivity tests regarding its internal setups and comparisons with other methods, respectively. Through a case study, the Pallas oil spill in the German Bight in 1998, it is demonstrated that this approach can help decision makers who search for an optimal strategy in multi-thread contingency problems and has a wider application potential in the field of integrated coastal zone management. PMID:16343765

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

    EPA Science Inventory

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

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

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

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

  7. Cyborg practices: call-handlers and computerised decision support systems in urgent and emergency care.

    PubMed

    Pope, Catherine; Halford, Susan; Turnbull, Joanne; Prichard, Jane

    2014-06-01

    This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice. PMID:24810726

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

    SciTech Connect

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

    2007-09-01

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

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

    SciTech Connect

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

    2011-11-15

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

  10. Design and realization of tourism spatial decision support system based on GIS

    NASA Astrophysics Data System (ADS)

    Ma, Zhangbao; Qi, Qingwen; Xu, Li

    2008-10-01

    In this paper, the existing problems of current tourism management information system are analyzed. GIS, tourism as well as spatial decision support system are introduced, and the application of geographic information system technology and spatial decision support system to tourism management and the establishment of tourism spatial decision support system based on GIS are proposed. System total structure, system hardware and software environment, database design and structure module design of this system are introduced. Finally, realization methods of this systemic core functions are elaborated.

  11. An Agent-Based Framework for Building Decision Support System in Supply Chain Management

    NASA Astrophysics Data System (ADS)

    Kazemi, A.; Fazel Zarandi, M. H.

    In this study, two scenarios are presented for solving Production-Distribution Panning Problem (PDPP) in a Decision Support System (DSS) framework. In the first scenario, a Traditional Decision Support System (TDSS) is presented for PDPP and a Genetic Algorithm (GA) is used for solving it. In the second scenario, a Multi-agent Decision Support System (MADSS) is considered for PDPP and three algorithms are used for solving it: Genetic Algorithm (GA), Tabu Search (TS) and Simulated Annealing (SA). Then an algorithm is suggested by using multi-agent system and A Teams concept. The obtained results reveal that the use of MADSS delivers better solutions to us.

  12. Hospital Information System Support for the Medical Decision Maker

    PubMed Central

    Mishelevich, David J.; Atkinson, Jack B.; Noland, Robert L.; Eisenberg, Jerry R.

    1981-01-01

    This paper describes the early stages in migration toward a comprehensive, on-line Hospital Information System with emphasis placed on the needs of the physician and other Medical Decision Makers. Such systems will properly put the computing power where it belongs: in the hands of the user, to the decision being made, to enhance health professional productivity and cost effectiveness. Thus we are evolving to such feedback to the physician in multiple dimensions, whether previous orders and/or results, patient profiles, cost of item ordered, potential drug-drug and drug-laboratory test interactions, potential duplicate examinations, or other information are involved. Considerations for systems which can potentially meet these needs are outlined. Specific examples of characteristics of the IBM Patient Care System {PCS} are presented as a prototypical model. Critical components are the presence of relevant data and the human-engineered, user-cordial access to that data. Coverage is given to multiple existing and potential sources of clinically-significant data whether manual or automated instrument input are involved.

  13. Visual cluster analysis in support of clinical decision intelligence.

    PubMed

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

    2011-01-01

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

  14. Visual Cluster Analysis in Support of Clinical Decision Intelligence

    PubMed Central

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

    2011-01-01

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

  15. A health examination system integrated with clinical decision support system.

    PubMed

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2010-10-01

    Health examinations play a key role in preventive medicine. We propose a health examination system named Health Examination Automatic Logic System (HEALS) to assist clinical workers in improving the total quality of health examinations. Quality of automated inference is confirmed by the zero inference error where during 6 months and 14,773 cases. Automated inference time is less than one second per case in contrast to 2 to 5 min for physicians. The most significant result of efficiency evaluation is that 3,494 of 4,356 (80.2%) cases take less than 3 min per case for producing a report summary. In the evaluation of effectiveness, novice physicians got 18% improvement in making decisions with the assistance of our system. We conclude that a health examination system with a clinical decision system can greatly reduce the mundane burden on clinical workers and markedly improve the quality and efficiency of health examination tasks. PMID:20703626

  16. Assembling Tools and Data for Climate Model Decision Support

    NASA Astrophysics Data System (ADS)

    Batcheller, A. L.; VanWijngaarden, F.

    2011-12-01

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

  17. Multisensory decisions provide support for probabilistic number representations.

    PubMed

    Kanitscheider, Ingmar; Brown, Amanda; Pouget, Alexandre; Churchland, Anne K

    2015-06-01

    A large body of evidence suggests that an approximate number sense allows humans to estimate numerosity in sensory scenes. This ability is widely observed in humans, including those without formal mathematical training. Despite this, many outstanding questions remain about the nature of the numerosity representation in the brain. Specifically, it is not known whether approximate numbers are represented as scalar estimates of numerosity or, alternatively, as probability distributions over numerosity. In the present study, we used a multisensory decision task to distinguish these possibilities. We trained human subjects to decide whether a test stimulus had a larger or smaller numerosity compared with a fixed reference. Depending on the trial, the numerosity was presented as either a sequence of visual flashes or a sequence of auditory tones, or both. To test for a probabilistic representation, we varied the reliability of the stimulus by adding noise to the visual stimuli. In accordance with a probabilistic representation, we observed a significant improvement in multisensory compared with unisensory trials. Furthermore, a trial-by-trial analysis revealed that although individual subjects showed strategic differences in how they leveraged auditory and visual information, all subjects exploited the reliability of unisensory cues. An alternative, nonprobabilistic model, in which subjects combined cues without regard for reliability, was not able to account for these trial-by-trial choices. These findings provide evidence that the brain relies on a probabilistic representation for numerosity decisions. PMID:25744886

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

    PubMed Central

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

    2014-01-01

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

  19. A proposed clinical decision support architecture capable of supporting whole genome sequence information.

    PubMed

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

    2014-04-01

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

  20. Pharmaceutical expenditure forecast model to support health policy decision making

    PubMed Central

    Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and objective With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods A model was built to assess policy scenarios’ impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Results Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Conclusions Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate

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

    ERIC Educational Resources Information Center

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

    2014-01-01

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

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

    ERIC Educational Resources Information Center

    Scott, Craig R.

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

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

    EPA Science Inventory

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

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

    SciTech Connect

    Liang, J.W.

    1996-12-01

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

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

    ERIC Educational Resources Information Center

    Wolfenden, Andrew

    2012-01-01

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

  6. A Web-Based Tool to Support Data-Based Early Intervention Decision Making

    ERIC Educational Resources Information Center

    Buzhardt, Jay; Greenwood, Charles; Walker, Dale; Carta, Judith; Terry, Barbara; Garrett, Matthew

    2010-01-01

    Progress monitoring and data-based intervention decision making have become key components of providing evidence-based early childhood special education services. Unfortunately, there is a lack of tools to support early childhood service providers' decision-making efforts. The authors describe a Web-based system that guides service providers…

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

    EPA Science Inventory

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

  8. AN INTEGRATED DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN-WATERSHEDS

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  10. Using Bayesian networks to support decision-focused information retrieval

    SciTech Connect

    Lehner, P.; Elsaesser, C.; Seligman, L.

    1996-12-31

    This paper has described an approach to controlling the process of pulling data/information from distributed data bases in a way that is specific to a persons specific decision making context. Our prototype implementation of this approach uses a knowledge-based planner to generate a plan, an automatically constructed Bayesian network to evaluate the plan, specialized processing of the network to derive key information items that would substantially impact the evaluation of the plan (e.g., determine that replanning is needed), automated construction of Standing Requests for Information (SRIs) which are automated functions that monitor changes and trends in distributed data base that are relevant to the key information items. This emphasis of this paper is on how Bayesian networks are used.

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

    SciTech Connect

    Tettelbach, C.G.

    1997-03-01

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

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

    PubMed

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

    2016-07-15

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

  13. Rule-based fault-tolerant flight control

    NASA Technical Reports Server (NTRS)

    Handelman, Dave

    1988-01-01

    Fault tolerance has always been a desirable characteristic of aircraft. The ability to withstand unexpected changes in aircraft configuration has a direct impact on the ability to complete a mission effectively and safely. The possible synergistic effects of combining techniques of modern control theory, statistical hypothesis testing, and artificial intelligence in the attempt to provide failure accommodation for aircraft are investigated. This effort has resulted in the definition of a theory for rule based control and a system for development of such a rule based controller. Although presented here in response to the goal of aircraft fault tolerance, the rule based control technique is applicable to a wide range of complex control problems.

  14. Rule-based and information-integration category learning in normal aging.

    PubMed

    Maddox, W Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M

    2010-08-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated processes, whereas information-integration is thought to involve implicit, striatally mediated processes. As a group, older adults showed rule-based and information-integration deficits. A series of models were applied that provided insights onto the type of strategy used to solve the task. Interestingly, when the analyses focused only on participants who used the task appropriate strategy in the final block of trials, the age-related rule-based deficit disappeared whereas the information-integration deficit remained. For this group of individuals, the final block information-integration deficit was due to less consistent application of the task appropriate strategy by older adults, and over the course of learning these older adults shifted from an explicit hypothesis-testing strategy to the task appropriate strategy later in learning. In addition, the use of the task appropriate strategy was associated with less interference and better inhibitory control for rule-based and information-information learning, whereas use of the task appropriate strategy was associated with greater working memory and better new verbal learning only for the rule-based task. These results suggest that normal aging impacts both forms of category learning and that there are some important similarities and differences in the explanatory locus of these deficits. The data also support a two-component model of information-integration category learning that includes a striatal component that mediated procedural-based learning, and a prefrontal cortical component that mediates the transition from hypothesis-testing to procedural-based strategies

  15. Nurses' acceptance of the decision support computer program for cancer pain management.

    PubMed

    Im, Eun-Ok; Chee, Wonshik

    2006-01-01

    This article describes nurses' acceptance of a decision support computer program for cancer pain management and explores the relationships between the nurses' acceptance and their sociodemographic characteristics. A feminist perspective was used as a theoretical guide for the research process. This was an Internet intervention study among 122 nurses working with cancer patients. Nurses' acceptance of the decision support computer program was measured using the Questionnaire for User Interaction Satisfaction. The data were analyzed using descriptive and inferential statistics, including analysis of variance and correlation analyses. There were significant differences in the total scores of user satisfaction by sex, religion, ethnicity, job title, and specialty. The results suggest that nurses do welcome decision support systems and that nurses' sociodemographic and professional characteristics should be considered in the development of decision support systems. PMID:16554693

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

    PubMed

    Sandell, Protik

    2007-01-01

    If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data. PMID:17583166

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

    EPA Science Inventory

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

  18. A Decision Support System for Managing a Diverse Portfolio of Technology Resources

    NASA Technical Reports Server (NTRS)

    Smith, J.

    2000-01-01

    This paper describes an automated decision support system designed to facilitate the management of a continuously changing portfolio of technologies as new technologies are deployed and older technologies are decommissioned.

  19. A Fourth-Generation Approach to Decision Support in a Private University.

    ERIC Educational Resources Information Center

    Glover, Robert H.

    1985-01-01

    Contrasts are made between application development strategies employed for online transaction processing and for decision support at the University of Hartford. Applications designed and implemented are described and current developments in the plan are discussed. (Author/MLW)

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

    EPA Science Inventory

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

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

    NASA Technical Reports Server (NTRS)

    Butler, Doug

    2009-01-01

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

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

    EPA Science Inventory

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

  3. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS (EPA/600/R-01/104)

    EPA Science Inventory

    Environmental decision support tools often provide information that predicts a multitude of different human health effects due to environmental stressors. Medical decision making and health economics offer many metrics that allow aggregation of these different health outcomes. Th...

  4. Learning interpretive decision algorithm for severe storm forecasting support

    SciTech Connect

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

    1983-01-01

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

  5. The research of the design of intelligent financial decision support system

    NASA Astrophysics Data System (ADS)

    Chen, Liyu; Chen, Qiang

    2011-02-01

    In accordance with the increasingly updating of information technology, the intelligent control technology is the integrated utilization of modern administrative technology and method. This article discusses problems of the objective of design, the development method, environment and overall structure of the intelligent financial decision support system in order to provide certain theories for the improvement of the intelligent financial decision support system as a reference.

  6. Decision-support systems for natural-hazards and land-management issues

    USGS Publications Warehouse

    Dinitz, Laura; Forney, William; Byrd, Kristin

    2012-01-01

    Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

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

    SciTech Connect

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

    1992-11-01

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

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

    SciTech Connect

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

    1992-11-01

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

  10. An Integrated Web-based Decision Support System in Disaster Risk Management

    NASA Astrophysics Data System (ADS)

    Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

    2012-04-01

    Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact

  11. Evaluating the use of a computerized clinical decision support system for asthma by pediatric pulmonologists

    PubMed Central

    Lomotan, Edwin A.; Hoeksema, Laura J.; Edmonds, Diana E.; Ramírez-Garnica, Gabriela; Shiffman, Richard N.; Horwitz, Leora I.

    2012-01-01

    Purpose To investigate use of a new guideline-based, computerized clinical decision support (CCDS) system for asthma in a pediatric pulmonology clinic of a large academic medical center. Methods We conducted a qualitative evaluation including review of electronic data, direct observation, and interviews with all nine pediatric pulmonologists in the clinic. Outcome measures included patterns of computer use in relation to patient care, and themes surrounding the relationship between asthma care and computer use. Results The pediatric pulmonologists entered enough data to trigger the decision support system in 397/445 (89.2%) of all asthma visits from January 2009 to May 2009. However, interviews and direct observations revealed use of the decision support system was limited to documentation activities after clinic sessions ended. Reasons for delayed use reflected barriers common to general medical care and barriers specific to subspecialty care. Subspecialist-specific barriers included the perceived high complexity of patients, the impact of subject matter expertise on the types of decision support needed, and unique workflow concerns such as the need to create letters to referring physicians. Conclusions Pediatric pulmonologists demonstrated low use of a computerized decision support system for asthma care because of a combination of general and subspecialist-specific factors. Subspecialist-specific factors should not be underestimated when designing guideline-based, computerized decision support systems for the subspecialty setting. PMID:22204897

  12. International online support to process optimisation and operation decisions.

    PubMed

    Onnerth, T B; Eriksson, J

    2002-01-01

    The information level at all technical facilities has developed from almost nothing 30-40 years ago to advanced IT--Information Technology--systems based on both chemical and mechanical on-line sensors for process and equipment. Still the basic part of information is to get the right data at the right time for the decision to be made. Today a large amount of operational data is available at almost any European wastewater treatment plant, from laboratory and SCADA. The difficult part is to determine which data to keep, which to use in calculations and how and where to make data available. With the STARcontrol system it is possible to separate only process relevant data to use for on-line control and reporting at engineering level, to optimise operation. Furthermore, the use of IT makes it possible to communicate internationally, with full access to the whole amount of data on the single plant. In this way, expert supervision can be both very local in local language e.g. Polish and at the same time very professional with Danish experts advising on Danish processes in Poland or Sweden where some of the 12 STARcontrol systems are running. PMID:11936670

  13. Indigenous knowledge as decision support tool in rainwater harvesting

    NASA Astrophysics Data System (ADS)

    Mbilinyi, B. P.; Tumbo, S. D.; Mahoo, H. F.; Senkondo, E. M.; Hatibu, N.

    Rainfall patterns in semi-arid areas are typically highly variable, both spatially and temporally. As a result, people who rely completely on rainwater for their survival have over the centuries developed indigenous knowledge/techniques to harvest rainwater. These traditional water-harvesting systems have been sustainable for centuries. The reason for this is that they are compatible with local lifestyles, local institutional patterns and local social systems. In order to develop sustainable strategies, it is therefore important to take into account of, and learn from, what local people already know and do, and to build on this. This paper explores how indigenous knowledge is used by farmers in the Makanya catchment, Kilimanjaro region, Tanzania to identify potential sites for rainwater harvesting (RWH). The paper draws on participatory research methods including focus group discussions, key informant interviews, field visits and participatory workshops. Initial findings indicate that farmers do hold a substantial amount of knowledge about the resources around them. As there are spatially typical aspects to indigenous knowledge, it could be extrapolated over a wider geographic extent. From the preliminary findings, it is being recommended that geographic information system (GIS) could be an important tool to collect and upscale the utility of diverse indigenous knowledge in the decision-making process.

  14. Decision support and data warehousing tools boost competitive advantage.

    PubMed

    Waldo, B H

    1998-01-01

    The ability to communicate across the care continuum is fast becoming an integral component of the successful health enterprise. As integrated delivery systems are formed and patient care delivery is restructured, health care professionals must be able to distribute, access, and evaluate information across departments and care settings. The Aberdeen Group, a computer and communications research and consulting organization, believes that "the single biggest challenge for next-generation health care providers is to improve on how they consolidate and manage information across the continuum of care. This involves building a strategic warehouse of clinical and financial information that can be shared and leveraged by health care professionals, regardless of the location or type of care setting" (Aberdeen Group, Inc., 1997). The value and importance of data and systems integration are growing. Organizations that create a strategy and implement DSS tools to provide decision-makers with the critical information they need to face the competition and maintain quality and costs will have the advantage. PMID:9592525

  15. Tolkku - a toolbox for decision support from condition monitoring data

    NASA Astrophysics Data System (ADS)

    Saarela, Olli; Lehtonen, Mikko; Halme, Jari; Aikala, Antti; Raivio, Kimmo

    2012-05-01

    This paper describes a software toolbox (a software library) designed for condition monitoring and diagnosis of machines. This toolbox implements both new methods and prior art and is aimed for practical down-to-earth data analysis work. The target is to improve knowledge of the operation and behaviour of machines and processes throughout their entire life-cycles. The toolbox supports different phases of condition based maintenance with tools that extract essential information and automate data processing. The paper discusses principles that have guided toolbox design and the implemented toolbox structure. Case examples are used to illustrate how condition monitoring applications can be built using the toolbox. In the first case study the toolbox is applied to fault detection of industrial centrifuges based on measured electrical current. The second case study outlines an application for centralized monitoring of a fleet of machines that supports organizational learning.

  16. A support for decision-making: cost-sensitive learning system.

    PubMed

    Bruha, I; Kocková, S

    1994-02-01

    This paper investigates a machine learning (ML) algorithm for supporting a decision-making system that is able to handle diagnostic problems. The input data are expressed by solved cases of patients' diagnoses, and the output is formed by a set of decision rules which may be directly exploited for a decision support. We have chosen the methodology of covering ML algorithms, namely the CN2 algorithm, as a starting point, and designed and implemented a certain extension of CN2 that comprises: advanced discretizing numerical attributes and incorporating attribute cost to economize the classification. PMID:8004148

  17. Methodical Approach to Developing a Decision Support System for Well Interventions Planning

    NASA Astrophysics Data System (ADS)

    Silich, V. A.; Savelev, A. O.; Isaev, A. N.

    2016-04-01

    The paper contains aspects of developing a decision support systems aimed for well interventions planning within the process of oil production engineering. The specific approach described by authors is based on system analysis methods and object model for system design. Declared number of problem-decision principles as follows: the principle of consolidated information area, the principle of integrated control, the principle of development process transparency. Also observed a set of models (class model, object model, attribute interdependence model, component model, coordination model) specified for designing decision support system for well intervention planning.

  18. An engineering approach to modelling, decision support and control for sustainable systems.

    PubMed

    Day, W; Audsley, E; Frost, A R

    2008-02-12

    Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems. PMID:17656345

  19. Bounded-time fault-tolerant rule-based systems

    NASA Technical Reports Server (NTRS)

    Browne, James C.; Emerson, Allen; Gouda, Mohamed; Miranker, Daniel; Mok, Aloysius; Rosier, Louis

    1990-01-01

    Two systems concepts are introduced: bounded response-time and self-stabilization in the context of rule-based programs. These concepts are essential for the design of rule-based programs which must be highly fault tolerant and perform in a real time environment. The mechanical analysis of programs for these two properties is discussed. The techniques are used to analyze a NASA application.

  20. Agricultural climate impacts assessment for economic modeling and decision support

    NASA Astrophysics Data System (ADS)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  1. Decision-support tools for the assessment process

    SciTech Connect

    Whelan, Gene; Pelton, Mitch A.; Dorow, Kevin E.

    2004-06-14

    A new software system is under development that provides a framework to link disparate assessment software and databases for site-specific, regional, or national analyses. This system represents the merger of the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES), which performs site-specific assessments, and Multi-media, Multi-pathway, Multi-receptor Risk Assessment (3MRA) methodology, which performs regional and national assessments. This Merged System is an icon-driven, site-layout platform, which represents an interactive means by which the user graphically constructs a conceptualization of the problem by visually expressing the assessment, indicating sources of contamination, contaminant travel pathways through the environment, linkages between contamination and people or wildlife, and impacts associated with the contamination. It processes data as part of a systems-based assessment and is an open-architecture, object-oriented framework, which contains ''sockets'' for a collection of databases and computer codes that will transparently simulate elements of transport, exposure, and risk assessment, including contaminant source and release to and through overland soils, vadose and saturated zones, air, surface water, food supply, intake human health impacts, sensitivity/uncertainty, ecological impacts, with the ability to expand into areas including Geographical Information System (GIS), remediation technology, cost analysis, Data Quality Objectives, life-cycle management, and conceptual site design. A user can choose from a list of models, and the assessment path forward can be visually presented, which describes the models and their linkages from source through receptor to the decision-making endpoint.

  2. Investigating Habitat Value in Support of Contaminant Remediation Decisions: Approach

    SciTech Connect

    Efroymson, Rebecca Ann; Peterson, Mark J; Welsh, Christopher John Edward; Druckenbrod, Daniel L; Ryon, Michael G; Smith, John G; Hargrove, William Walter; Giffen, Neil R; Roy, W Kelly; Quarles III, Harry Dewitt

    2008-01-01

    Habitat valuation methods are most often developed and used to prioritize candidate lands for conservation. In this study the intent of habitat valuation was to inform the decision-making process for remediation of chemical contaminants on specific lands or surface water bodies. Methods were developed to summarize dimensions of habitat value for six representative aquatic and terrestrial contaminated sites at the East Tennessee Technology Park (ETTP) on the US Department of Energy Oak Ridge Reservation in Oak Ridge, TN, USA. Several general valuation metrics were developed for three broad categories: site use by groups of organisms, site rarity, and use value added from spatial context. Examples of use value metrics are taxa richness, a direct measure of number of species that inhabit an area, complexity of habitat structure, an indirect measure of potential number of species that may use the area, and land use designation, a measure of the length of time that the area will be available for use. Measures of rarity included presence of rare species or communities. Examples of metrics for habitat use value added from spatial context included similarity or complementarity of neighboring habitat patches and presence of habitat corridors. More specific metrics were developed for groups of organisms in contaminated streams, ponds, and terrestrial ecosystems. For each of these metrics, cutoff values for high, medium, and low habitat value were suggested, based on available information on distributions of organisms and landscape features, as well as habitat use information. A companion paper describes the implementation of these habitat valuation metrics and scoring criteria in the remedial investigation for ETTP.

  3. Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

    NASA Astrophysics Data System (ADS)

    Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

    2014-05-01

    Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

  4. Identifying the decision to be supported: a review of papers from environmental modelling and software

    USGS Publications Warehouse

    Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

    2012-01-01

    Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for

  5. Overcoming deficiencies of the rule-based medical expert system.

    PubMed

    Hughes, C A; Gose, E E; Roseman, D L

    1990-05-01

    One of the current deficiencies of the rule-based expert system is its static nature. As these systems are applied to medicine, this shortcoming becomes accentuated by: the rapid speed at which new knowledge is generated, the regional differences associated with the expression of many diseases, and the rate at which patient demographics and disease incidence change over time. This research presents a solution to the static nature of the rule-based expert system by proposing a hybrid system. This system consists of an expert system and a statistical analysis system linked to a patient database. The additional feature of a rule base manager which initiates automatic database analysis to refresh the statistical correlation of each rule ensures a dynamic, current, statistically accurate rule base. The philosophical differences between data and knowledge are also addressed as they apply to this type of hybrid system. The system is then used to generate four rule bases from different knowledge sources. These rule bases are then compared. PMID:2401135

  6. A rule based computer aided design system

    NASA Technical Reports Server (NTRS)

    Premack, T.

    1986-01-01

    A Computer Aided Design (CAD) system is presented which supports the iterative process of design, the dimensional continuity between mating parts, and the hierarchical structure of the parts in their assembled configuration. Prolog, an interactive logic programming language, is used to represent and interpret the data base. The solid geometry representing the parts is defined in parameterized form using the swept volume method. The system is demonstrated with a design of a spring piston.

  7. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation.

    PubMed

    Linan, Margaret K; Sottara, Davide; Freimuth, Robert R

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines. PMID:26958298

  8. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation

    PubMed Central

    Linan, Margaret K.; Sottara, Davide; Freimuth, Robert R.

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines. PMID:26958298

  9. Information System Engineering Supporting Observation, Orientation, Decision, and Compliant Action

    NASA Astrophysics Data System (ADS)

    Georgakopoulos, Dimitrios

    The majority of today's software systems and organizational/business structures have been built on the foundation of solving problems via long-term data collection, analysis, and solution design. This traditional approach of solving problems and building corresponding software systems and business processes, falls short in providing the necessary solutions needed to deal with many problems that require agility as the main ingredient of their solution. For example, such agility is needed in responding to an emergency, in military command control, physical security, price-based competition in business, investing in the stock market, video gaming, network monitoring and self-healing, diagnosis in emergency health care, and many other areas that are too numerous to list here. The concept of Observe, Orient, Decide, and Act (OODA) loops is a guiding principal that captures the fundamental issues and approach for engineering information systems that deal with many of these problem areas. However, there are currently few software systems that are capable of supporting OODA. In this talk, we provide a tour of the research issues and state of the art solutions for supporting OODA. In addition, we provide specific examples of OODA solutions we have developed for the video surveillance and emergency response domains.

  10. Evaluating Michigan's community hospital access: spatial methods for decision support

    PubMed Central

    Messina, Joseph P; Shortridge, Ashton M; Groop, Richard E; Varnakovida, Pariwate; Finn, Mark J

    2006-01-01

    approaches enable policymakers to identify under-served areas. Ultimately this paper is concerned with the intersection of spatial analysis and policymaking. Using the best scientific practice to identify locations of under-served populations based on many factors provides policymakers with a powerful tool for making good decisions. PMID:16995948

  11. Geospatial Data Fusion and Multigroup Decision Support for Surface Water Quality Management

    NASA Astrophysics Data System (ADS)

    Sun, A. Y.; Osidele, O.; Green, R. T.; Xie, H.

    2010-12-01

    Social networking and social media have gained significant popularity and brought fundamental changes to many facets of our everyday life. With the ever-increasing adoption of GPS-enabled gadgets and technology, location-based content is likely to play a central role in social networking sites. While location-based content is not new to the geoscience community, where geographic information systems (GIS) are extensively used, the delivery of useful geospatial data to targeted user groups for decision support is new. Decision makers and modelers ought to make more effective use of the new web-based tools to expand the scope of environmental awareness education, public outreach, and stakeholder interaction. Environmental decision processes are often rife with uncertainty and controversy, requiring integration of multiple sources of information and compromises between diverse interests. Fusing of multisource, multiscale environmental data for multigroup decision support is a challenging task. Toward this goal, a multigroup decision support platform should strive to achieve transparency, impartiality, and timely synthesis of information. The latter criterion often constitutes a major technical bottleneck to traditional GIS-based media, featuring large file or image sizes and requiring special processing before web deployment. Many tools and design patterns have appeared in recent years to ease the situation somewhat. In this project, we explore the use of Web 2.0 technologies for “pushing” location-based content to multigroups involved in surface water quality management and decision making. In particular, our granular bottom-up approach facilitates effective delivery of information to most relevant user groups. Our location-based content includes in-situ and remotely sensed data disseminated by NASA and other national and local agencies. Our project is demonstrated for managing the total maximum daily load (TMDL) program in the Arroyo Colorado coastal river basin

  12. Rule-based Cross-matching of Very Large Catalogs

    NASA Astrophysics Data System (ADS)

    Ogle, P. M.; Mazzarella, J.; Ebert, R.; Fadda, D.; Lo, T.; Terek, S.; Schmitz, M.; NED Team

    2015-09-01

    The NASA Extragalactic Database (NED) has deployed a new rule-based cross-matching algorithm called Match Expert (MatchEx), capable of cross-matching very large catalogs (VLCs) with >10 million objects. MatchEx goes beyond traditional position-based cross-matching algorithms by using other available data together with expert logic to determine which candidate match is the best. Furthermore, the local background density of sources is used to determine and minimize the false-positive match rate and to estimate match completeness. The logical outcome and statistical probability of each match decision is stored in the database and may be used to tune the algorithm and adjust match parameter thresholds. For our first production run, we cross-matched the GALEX All Sky Survey Catalog (GASC), containing nearly 40 million NUV-detected sources, against a directory of 180 million objects in NED. Candidate matches were identified for each GASC source within a 7''.5 radius. These candidates were filtered on position-based matching probability and on other criteria including object type and object name. We estimate a match completeness of 97.6% and a match accuracy of 99.75%. Over the next year, we will be cross-matching over 2 billion catalog sources to NED, including the Spitzer Source List, the 2MASS point-source catalog, AllWISE, and SDSS DR 10. We expect to add new capabilities to filter candidate matches based on photometry, redshifts, and refined object classifications. We will also extend MatchEx to handle more heterogenous datasets federated from smaller catalogs through NED's literature pipeline.

  13. Testing an Irrigation Decision Support Tool for California Specialty Crops

    NASA Astrophysics Data System (ADS)

    Johnson, L.; Cahn, M.; Benzen, S.; Zaragoza, I.; Murphy, L.; Melton, F. S.; Martin, F.; Quackenbush, A.; Lockhart, T.

    2015-12-01

    Estimation of crop evapotranspiration supports efficiency of irrigation water management, which in turn can mitigate nitrate leaching, groundwater depletion, and provide energy savings. Past research in California and elsewhere has revealed strong relationships between photosynthetically active vegetation fraction (Fc) and crop evapotranspiration (ETc). Additional research has shown the potential of monitoring Fc by satellite remote sensing. The U.C. Cooperative Extension developed and operates CropManage (CM) as on-line database irrigation (and nitrogen) scheduling tool. CM accounts for the rapid growth and typically brief cycle of cool-season vegetables, where Fc and fraction of reference ET can change daily during canopy development. The model automates crop water requirement calculations based on reference ET data collected by California Dept. Water Resources. Empirically-derived equations are used to estimate daily Fc time-series for a given crop type primarily as a function of planting date and expected harvest date. An application programming interface (API) is under development to provide a check on modeled Fc of current crops and facilitate CM expansion to new crops. The API will enable CM to extract field scale Fc observations from NASA's Satellite Irrigation Management Support (SIMS). SIMS is mainly Landsat based and currently monitors Fc over about 8 million irrigation acres statewide, with potential for adding data from ESA/Sentinel for improved temporal resolution. In the current study, a replicated irrigation trial was performed on romaine lettuce at the USDA Agricultural Research Station in Salinas, CA. CropManage recommendations were used to guide water treatments by drip irrigation at 50%, 75%, 100% ETc replacement levels, with an added treatment at 150% ET representing grower standard practice. Experimental results indicate that yields from the 100% and 150% treatments were not significantly different and were in-line with industry average, while

  14. Enabling Cross-Platform Clinical Decision Support through Web-Based Decision Support in Commercial Electronic Health Record Systems: Proposal and Evaluation of Initial Prototype Implementations

    PubMed Central

    Zhang, Mingyuan; Velasco, Ferdinand T.; Musser, R. Clayton; Kawamoto, Kensaku

    2013-01-01

    Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

  15. Enabling cross-platform clinical decision support through Web-based decision support in commercial electronic health record systems: proposal and evaluation of initial prototype implementations.

    PubMed

    Zhang, Mingyuan; Velasco, Ferdinand T; Musser, R Clayton; Kawamoto, Kensaku

    2013-01-01

    Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

  16. Personalised Multi-Criterial Online Decision Support for Siblings Considering Stem Cell Donation: An Interactive Aid.

    PubMed

    Kaltoft, Mette Kjer; Salkeld, Glenn; Dowie, Jack

    2016-01-01

    Person-centred decision support combines the best available information on the considerations that matter to the individual, with the importance the person attaches to those considerations. Nurses and other health professionals can benefit from being able to draw on this support within a clinical conversation. A case study and storyline on four siblings facing a transplant coordinator's call to donate stem cells to their brother [1] is 'translated' and used to demonstrate how an interactive multi-criteria aid can be developed for each within a conversational mode. The personalized dialogue and decision aid are accessible online for interaction. Each sibling's decision exemplifies the communication including physical and psychosocial complexities within any decision cascade from call-to-test and to donate, if compatible. A shared template can embrace the informational and ethical aspects of a decision. By interactive decision support within a clinical conversation, each stakeholder can gain a personalised opinion, as well as increased generic health decision literacy [2]. PMID:27332459

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

    PubMed

    Spratt, Trevor; Devaney, John; Hayes, David

    2015-11-01

    The aims of this study were to identify the themes Social Workers regard as important in supporting decisions to remove children from, or return them to, the care of their parents. To further elicit underlying hypotheses that are discernible in interpretation of evidence. A case study, comprising a two-part vignette with a questionnaire, recorded demographic information, child welfare attitudes and risk assessments, using scales derived from standardised instruments, was completed by 202 Social Workers in Northern Ireland. There were two manipulated variables, mother's attitude to removal and child's attitude to reunification 2 years later. In this paper we use data derived from respondents' qualitative comments explaining their reasoning for in and out of home care decisions. Some 60.9% of respondent's chose the parental care option at part one, with 94% choosing to have the child remain in foster care at part two. The manipulated variables were found to have no significant statistical effect. However, three underlying hypotheses were found to underpin decisions; (a) child rescue, (b) kinship defence and (c) a hedged position on calculation of risk subject to further assessment. Reasoning strategies utilised by social workers to support their decision making suggest that they tend to selectively interpret information either positively or negatively to support pre-existing underlying hypotheses. This finding is in keeping with the literature on 'confirmation bias.' The research further draws attention to the need to incorporate open questions in quantitative studies, to help guard against surface reading of data, which often does not 'speak for itself.' PMID:25687965

  18. Remedial action assessment system: Decision support for environmental cleanup

    SciTech Connect

    Pennock, K.A.; Bohn, S.; Franklin, A.L.

    1991-11-01

    A large number of hazardous waste sites across the United States await treatment. Waste sites can be physically complex entities composed of multiple, possibly interacting contaminants distributed throughout one or more media. The sites may be active as well with contaminants escaping through one or more potential escape paths. Treatment of these sites requires a long and costly commitment involving the coordination of activities among several waste treatment professionals. In order to reduce the cost and time required for the specification of treatment at these waste sites. The Remedial Action Assessment System (RAAS) was proposed. RAAS is an automated information management system which utilizes a combination of expert reasoning and numerical models to produce the combinations of treatment technologies, known as treatment trains, which satisfy the treatment objectives of a particular site. In addition, RAAS supports the analysis of these trains with regard to effectiveness and cost so that the viable treatment trains can be measured against each other. The Remedial Action Assessment System is a hybrid system designed and constructed using object-oriented tools and techniques. RAAS is advertised as a hybrid system because it combines, in integral fashion, numerical computing (primarily quantitative models) with expert system reasoning. An object-oriented approach was selected due to many of its inherent advantages, among these the naturalness of modeling physical objects and processes.

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

    NASA Astrophysics Data System (ADS)

    Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

    2012-12-01

    We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.

  20. Association-rule-based tuberculosis disease diagnosis

    NASA Astrophysics Data System (ADS)

    Asha, T.; Natarajan, S.; Murthy, K. N. B.

    2010-02-01

    Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air and attacks low immune bodies such as patients with Human Immunodeficiency Virus (HIV). This work focuses on finding close association rules, a promising technique in Data Mining, within TB data. The proposed method first normalizes of raw data from medical records which includes categorical, nominal and continuous attributes and then determines Association Rules from the normalized data with different support and confidence. Association rules are applied on a real data set containing medical records of patients with TB obtained from a state hospital. The rules determined describes close association between one symptom to another; as an example, likelihood that an occurrence of sputum is closely associated with blood cough and HIV.

  1. Secure Medical Diagnosis Using Rule Based Mining

    NASA Astrophysics Data System (ADS)

    Saleem Durai, M. A.; Sriman Narayana Iyengar, N. Ch.

    Security is the governing dynamics of all walks of life. Here we propose a secured medical diagnosis system. Certain specific rules are specified implicitly by the designer of the expert system and then symptoms for the diseases are obtained from the users and by using the pre defined confidence and support values we extract a threshold value which is used to conclude on a particular disease and the stage using Rule Mining. "THINK" CAPTCHA mechanism is used to distinguish between the human and the robots thereby eliminating the robots and preventing them from creating fake accounts and spam's. A novel image encryption mechanism is designed using genetic algorithm to encrypt the medical images thereby storing and sending the image data in a secured manner.

  2. Medical alert management: a real-time adaptive decision support tool to reduce alert fatigue.

    PubMed

    Lee, Eva K; Wu, Tsung-Lin; Senior, Tal; Jose, James

    2014-01-01

    With the adoption of electronic medical records (EMRs), drug safety alerts are increasingly recognized as valuable tools for reducing adverse drug events and improving patient safety. However, even with proper tuning of the EMR alert parameters, the volume of unfiltered alerts can be overwhelming to users. In this paper, we design an adaptive decision support tool in which past cognitive overriding decisions of users are learned, adapted and used for filtering actions to be performed on current alerts. The filters are designed and learned based on a moving time window, number of alerts, overriding rates, and monthly overriding fluctuations. Using alerts from two separate years to derive filters and test performance, predictive accuracy rates of 91.3%-100% are achieved. The moving time window works better than a static training approach. It allows continuous learning and capturing of the most recent decision characteristics and seasonal variations in drug usage. The decision support system facilitates filtering of non-essential alerts and adaptively learns critical alerts and highlights them prominently to catch providers' attention. The tool can be plugged into an existing EMR system as an add-on, allowing real-time decision support to users without interfering with existing EMR functionalities. By automatically filtering the alerts, the decision support tool mitigates alert fatigue and allows users to focus resources on potentially vital alerts, thus reducing the occurrence of adverse drug events. PMID:25954391

  3. A Decision Support Framework for Genomically Informed Investigational Cancer Therapy

    PubMed Central

    Johnson, Amber; Holla, Vijaykumar; Bailey, Ann Marie; Brusco, Lauren; Chen, Ken; Routbort, Mark; Patel, Keyur P.; Zeng, Jia; Kopetz, Scott; Davies, Michael A.; Piha-Paul, Sarina A.; Hong, David S.; Eterovic, Agda Karina; Tsimberidou, Apostolia M.; Broaddus, Russell; Bernstam, Elmer V.; Shaw, Kenna R.; Mendelsohn, John; Mills, Gordon B.

    2015-01-01

    Rapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient’s molecular profile, including molecular characterization of the tumor and the patient’s germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a “cancer gene” at the level of a specific variant in order to discriminate so-called “drivers” from “passengers.” Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially “actionable.” At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients. PMID:25863335

  4. Quantitative ultrasound texture analysis for clinical decision making support

    NASA Astrophysics Data System (ADS)

    Wu, Jie Ying; Beland, Michael; Konrad, Joseph; Tuomi, Adam; Glidden, David; Grand, David; Merck, Derek

    2015-03-01

    We propose a general ultrasound (US) texture-analysis and machine-learning framework for detecting the presence of disease that is suitable for clinical application across clinicians, disease types, devices, and operators. Its stages are image selection, image filtering, ROI selection, feature parameterization, and classification. Each stage is modular and can be replaced with alternate methods. Thus, this framework is adaptable to a wide range of tasks. Our two preliminary clinical targets are hepatic steatosis and adenomyosis diagnosis. For steatosis, we collected US images from 288 patients and their pathology-determined values of steatosis (%) from biopsies. Two radiologists independently reviewed all images and identified the region of interest (ROI) most representative of the hepatic echotexture for each patient. To parameterize the images into comparable quantities, we filter the US images at multiple scales for various texture responses. For each response, we collect a histogram of pixel features within the ROI, and parameterize it as a Gaussian function using its mean, standard deviation, kurtosis, and skew to create a 36-feature vector. Our algorithm uses a support vector machine (SVM) for classification. Using a threshold of 10%, we achieved 72.81% overall accuracy, 76.18% sensitivity, and 65.96% specificity in identifying steatosis with leave-ten-out cross-validation (p<0.0001). Extending this framework to adenomyosis, we identified 38 patients with MR-confirmed findings of adenomyosis and previous US studies and 50 controls. A single rater picked the best US-image and ROI for each case. Using the same processing pipeline, we obtained 76.14% accuracy, 86.00% sensitivity, and 63.16% specificity with leave-one-out cross-validation (p<0.0001).

  5. Modelling Vague Knowledge for Decision Support in Planning Archaeological Prospections

    NASA Astrophysics Data System (ADS)

    Boos, S.; Hornung, S.; Müller, H.

    2012-07-01

    Most archaeological predictive models lack significance because fuzziness of data and uncertainty in knowledge about human behaviour and natural processes are hardly ever considered. One possibility to cope with such uncertainties is utilization of probability based approaches like Bayes Theorem or Dempster-Shafer-Theory. We analyzed an area of 50 km2 in Rhineland Palatinate (Germany) near a Celtic oppidum by use of Dempster-Shafer's theory of evidence for predicting spatial probability distribution of archaeological sites. This technique incorporates uncertainty by assigning various weights of evidence to defined variables, in that way estimating the probability for supporting a specific hypothesis (in our case the hypothesis presence or absence of a site). Selection of variables for our model relied both on assumptions about settlement patterns and on statistically tested relationships between known archaeological sites and environmental factors. The modelling process was conducted in a Geographic Information System (GIS) by generating raster-based likelihood surfaces. The corresponding likelihood surfaces were aggregated to a final weight of evidence surface, which resulted in a likelihood value for every single cell of being a site or a non-site. Finally the result was tested against a database of known archaeological sites for evaluating the gain of the model. For the purpose of enhancing the gain of our model and sharpening our criteria we used a two-step approach to improve the modelling of former settlement strategies in our study area. Applying the developed model finally yielded a 100 percent success rate of known archaeological sites located in predicted high potential areas.

  6. Use of Simulation to Study Nurses' Acceptance and Nonacceptance of Clinical Decision Support Suggestions.

    PubMed

    Sousa, Vanessa E C; Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Yao, Yingwei; Johnson, Andrew; Wilkie, Diana J; Keenan, Gail M

    2015-10-01

    Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice. PMID:26361268

  7. Telemonitoring in heart failure patients with clinical decision support to optimize medication doses based on guidelines.

    PubMed

    Kropf, Martin; Modre-Osprian, Robert; Hayn, Dieter; Fruhwald, Friedrich; Schreier, Günter

    2014-01-01

    The European Society of Cardiology guidelines for heart failure management are based on strong evidence that adherence to optimal medication is beneficial for heart failure patients. Telemonitoring with integrated clinical decision support enables physicians to adapt medication dose based on up to date vital parameters and reduces the number of hospital visits needed solely for up-titration of heart failure medication. Although keeping track of weight and blood pressure changes is recommended during unstable phases, e.g. post-discharge and during up-titration of medication, guidelines are rather vague regarding telehealth aspects. In this paper, we focus on the evaluation of a clinical decision support system for adaption of heart failure medication and for detecting early deteriorations through monitoring of blood pressure, heart rate and weight changes. This clinical decision support system is currently used in INTENSE-HF, a large scale telemonitoring trial with heart failure patients. The aim of this paper was to apply the decision support algorithm to an existing telemonitoring dataset, to assess the ability of the decision support concept to adhere to the guidelines and to discuss its limitations and potential improvements. PMID:25570663

  8. The application of decision analysis to life support research and technology development

    NASA Technical Reports Server (NTRS)

    Ballin, Mark G.

    1994-01-01

    Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

  9. NASA's past, current and potential future support in bringing climate projection information to the decision support level

    NASA Astrophysics Data System (ADS)

    Lee, T. J.

    2015-12-01

    It is common that we use global climate models or Earth system models to perform climate projection into the future. Because of the long integration time and the tremendous computing resources required for such a projection, the model resolution is typically not at a spatial scale fine enough for climate assessment or decision support purposes. A number of "downscaling technologies" have been developed over the years to bring the climate projection information to the local level for management and policy decision support purposes. In the past couple of years, NASA supported a number of regional to local climate projection activities: NASA Climate Adaption Science Investigators focused on climate resilience at NASA center level, National Climate Assessment (NCA) Capacity Building focused on data sets and tools to support NCA, NCA Indicators focused on creating simple indicators specifically designed for decision support, Assessing the Fidelity of Dynamical Downscaling with the NASA Unifies-WRF Model focused on understanding the credibility of dynamical downscaling technique using a regional climate model. All of these projects have a component in creating or using downscaled climate information. With the consequence of climate change beginning to emerge, there is a continuous need to better quantify the quality of downscaled climate projections. In this talk I will give an overview on NASA's efforts to understand the various techniques, the limitations including the risks of using these techniques, and finally, I will provide a view on possible future researches in this area.

  10. Design of decision support system when undertaking medical-diagnostic action

    NASA Astrophysics Data System (ADS)

    Povoroznyuk, Anatoliy I.; Filatova, Anna E.; Surtel, Wojciech; Burlibay, Aron; Zhassandykyzy, Maral

    2015-12-01

    In the work the formalization of the problem of diagnostic and treatment activities (DTA) steps complex estimation for increasing of their efficiency and minimization of the risk of doctor's mistakes was completed. The decision support system during conducting of DTA based on formalizations of steps of DTA performing with theirs complex estimation was developed that allows to minimize the risks of doctor's mistakes, raise validity of decisions.

  11. Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey

    PubMed Central

    Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan

    2013-01-01

    The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259

  12. Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

    NASA Astrophysics Data System (ADS)

    Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

    2015-04-01

    Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

  13. Using multicriteria decision analysis to support research priority setting in biomedical translational research projects.

    PubMed

    de Graaf, Gimon; Postmus, Douwe; Buskens, Erik

    2015-01-01

    Translational research is conducted to achieve a predefined set of economic or societal goals. As a result, investment decisions on where available resources have the highest potential in achieving these goals have to be made. In this paper, we first describe how multicriteria decision analysis can assist in defining the decision context and in ensuring that all relevant aspects of the decision problem are incorporated in the decision making process. We then present the results of a case study to support priority setting in a translational research consortium aimed at reducing the burden of disease of type 2 diabetes. During problem structuring, we identified four research alternatives (primary, secondary, tertiary microvascular, and tertiary macrovascular prevention) and a set of six decision criteria. Scoring of these alternatives against the criteria was done using a combination of expert judgement and previously published data. Lastly, decision analysis was performed using stochastic multicriteria acceptability analysis, which allows for the combined use of numerical and ordinal data. We found that the development of novel techniques applied in secondary prevention would be a poor investment of research funds. The ranking of the remaining alternatives was however strongly dependent on the decision maker's preferences for certain criteria. PMID:26495288

  14. A concept-based medication vocabulary: an essential requirement for pharmacy decision support.

    PubMed

    Broverman, C; Kapusnik-Uner, J; Shalaby, J; Sperzel, D

    1998-04-01

    The impact of adverse drug events (ADEs) on the cost and quality of health care today is indisputable. A significant portion of these events can be detected and prevented with computerized pharmacy decision support systems. Challenges to the successful implementation of decision support systems include availability and quality of patient data and the accessibility of drug information that can be integrated programmatically on a patient-specific basis. An additional related challenge is establishing the vocabulary (i.e., codes, terms, and meanings) to be used for the representation, exchange, and automation of drug information and clinical functions. A central argument of this article is that a concept-based medication vocabulary needs to be created in order to facilitate the development of pharmacy decision support. We address the medication vocabulary challenge by defining a specific concept-based model of drugs as the basis for a standardized medication terminology. PMID:10184876

  15. Designing Tools for Supporting User Decision-Making in e-Commerce

    NASA Astrophysics Data System (ADS)

    Sutcliffe, Alistair; Al-Qaed, Faisal

    The paper describes a set of tools designed to support a variety of user decision-making strategies. The tools are complemented by an online advisor so they can be adapted to different domains and users can be guided to adopt appropriate tools for different choices in e-commerce, e.g. purchasing high-value products, exploring product fit to users’ needs, or selecting products which satisfy requirements. The tools range from simple recommenders to decision support by interactive querying and comparison matrices. They were evaluated in a scenario-based experiment which varied the users’ task and motivation, with and without an advisor agent. The results show the tools and advisor were effective in supporting users and agreed with the predictions of ADM (adaptive decision making) theory, on which the design of the tools was based.

  16. Clinical Decision Support using a Terminology Server to improve Patient Safety.

    PubMed

    Garcia-Jimenez, Alba; Moreno-Conde, Alberto; Martínez-García, Alicia; Marín-León, Ignacio; Medrano-Ortega, Francisco Javier; Parra-Calderón, Carlos L

    2015-01-01

    Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario. PMID:25991120

  17. Tablet-based patient monitoring and decision support systems in hospital care.

    PubMed

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Linden, Maria

    2015-08-01

    Remote patient monitoring with evidence-based decision support is revolutionizing healthcare. This novel approach could enable both patients and healthcare providers to improve quality of care and reduce costs. Clinicians can also view patients' data within the hospital network on tablet computers as well as other ubiquitous devices. Today, a wide range of applications are available on tablet computers which are increasingly integrating into the healthcare mainstream as clinical decision support systems. Despite the benefits of tablet-based healthcare applications, there are concerns around the accuracy, security and stability of such applications. In this study, we developed five tablet-based application screens for remote patient monitoring at hospital care settings and identified related issues and challenges. The ultimate aim of this research is to integrate decision support algorithms into the monitoring system in order to improve inpatient care and the effectiveness of such applications. PMID:26736485

  18. Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

    USGS Publications Warehouse

    Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi

    2006-01-01

    There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

  19. Concurrent validity of a rule-based system.

    PubMed

    Hirsch, M; Chang, B L; Jensen, K

    1993-01-01

    The purpose of this project was to test the concurrent validity of the diagnoses recommended by a rule-based expert system. Concurrent validity was determined first by comparing the expert system's computerized diagnostic recommendations with that of a Clinical Nurse Specialist (CNS Assessor) who assessed the patient, and secondly by comparing the expert system's candidate diagnoses with those of a panel of 10 clinical nurse specialists (CNS Panel). The expert system rule base for generating diagnoses was programmed for some of the most common nursing diagnoses (Metzger & Hiltunen, 1987) including: alteration in comfort, acute pain; impaired physical mobility; sleep pattern disturbance; impairment of skin integrity and self-care deficit (bathing, feeding, toileting, and dressing). Activity intolerance and potential for infection were also programmed as diagnostic possibilities in the rule base. PMID:8069751

  20. Clinical decision support must be useful, functional is not enough: a qualitative study of computer-based clinical decision support in primary care

    PubMed Central

    2012-01-01

    Background Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. Methods The setting was a Finnish primary health care organization with 48 professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. Results The content of the guidance is a significant feature of the primary care professional’s intention to use eCDS. The decisive reason for using or not using the eCDS is its perceived usefulness. Functional characteristics such as speed and ease of use are important but alone these are not enough. Specific information technology, professional, patient and environment features can help or hinder the use. Conclusions Primary care professionals have to perceive eCDS guidance useful for their work before they use it. PMID:23039113

  1. IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

    NASA Astrophysics Data System (ADS)

    Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

    2013-04-01

    A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

  2. Integrating decision support, based on the Arden Syntax, in a clinical laboratory environment.

    PubMed Central

    Johansson, B.; Bergqvist, Y.

    1993-01-01

    A clinical decision support system prototype have been developed in the clinical laboratory environment. The knowledge base consists of Medical Logic Modules, written in the Arden Syntax, and the work describes how these modules can be written, evoked and executed in a system, that is integrated with a laboratory information system, and facilitate real time validation of laboratory data. Tools and methods for building a decision support system are described and design aspects, such as database access, system validation and platform independence, are discussed. PMID:8130502

  3. A decision support system for map projections of small scale data

    USGS Publications Warehouse

    Finn, Michael P.; Usery, E. Lynn; Posch, Stephan T.; Seong, Jeong Chang

    2004-01-01

    The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

  4. Disaster Response and Decision Support in Partnership with the California Earthquake Clearinghouse

    NASA Astrophysics Data System (ADS)

    Glasscoe, M. T.; Rosinski, A.; Vaughan, D.; Morentz, J.

    2014-12-01

    Getting the right information to the right people at the right time is critical during a natural disaster. E-DECIDER (Emergency Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response) is a NASA decision support system designed to produce remote sensing and geophysical modeling data products that are relevant to the emergency preparedness and response communities and serve as a gateway to enable the delivery of NASA decision support products to these communities. The E-DECIDER decision support system has several tools, services, and products that have been used to support end-user exercises in partnership with the California Earthquake Clearinghouse since 2012, including near real-time deformation modeling results and on-demand maps of critical infrastructure that may have been potentially exposed to damage by a disaster. E-DECIDER's underlying service architecture allows the system to facilitate delivery of NASA decision support products to the Clearinghouse through XchangeCore Web Service Data Orchestration that allows trusted information exchange among partner agencies. This in turn allows Clearinghouse partners to visualize data products produced by E-DECIDER and other NASA projects through incident command software such as SpotOnResponse or ArcGIS Online.

  5. Supplementing Global Narratives with National to Regional Scale Scenarios for Decision Support (Invited)

    NASA Astrophysics Data System (ADS)

    Moss, R. H.; Patwardhan, A.

    2013-12-01

    This presentation examines decision-making contexts to clarify how globally-oriented scenarios of future demographic, economic, and social conditions (the Shared Socioeconomic Pathways -- SSPs) can be extended or nested with scenarios that are targeted on uncertainties of more immediate concern to decision makers. A number of use cases are explored to identify key uncertainties and the attributes of scenarios that would help decision-makers think through the implications of these uncertainties. These uncertainties concern future conditions at national to regional spatial and governance scales regarding factors outside the locus of control of the decision makers. The exogenous factors that need to be represented in scenarios affect supply and demand of relevant commodities/products, institutional conditions, and vulnerability. They include: demographics & societal conditions; economic growth; policy and institutional context (including public & private responses); technology/resource price and performance; and climate/environmental outcomes. The presentation will explore development of decision-support oriented scenarios that are built from the 'bottom-up' and highlight points of divergence in national/regional social and economic conditions. The authors draw preliminary conclusions regarding methods for nesting decision support scenarios in high-level global narratives.

  6. Translational Cognition for Decision Support in Critical Care Environments: A Review

    PubMed Central

    Patel, Vimla L.; Zhang, Jiajie; Yoskowitz, Nicole A.; Green, Robert; Sayan, Osman R.

    2008-01-01

    The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers. PMID:18343731

  7. Quality of Online Information to Support Patient Decision-Making in Breast Cancer Surgery

    PubMed Central

    Bruce, Jordan G.; Tucholka, Jennifer L.; Steffens, Nicole M.; Neuman, Heather B.

    2015-01-01

    Background Breast cancer patients commonly use the internet as an information resource. Our objective was to evaluate the quality of online information available to support patients facing a decision for breast surgery. Methods Breast cancer surgery-related queries were performed (Google and Bing), and reviewed for content pertinent to breast cancer surgery. The DISCERN instrument was used to evaluate websites’ structural components that influence publication reliability and ability of information to support treatment decision-making. Scores of 4/5 were considered “good”. Results 45 unique websites were identified. Websites satisfied a median 5/9 content questions. Commonly omitted topics included: having a choice between breast conservation and mastectomy (67%) and potential for 2nd surgery to obtain negative margins after breast conservation (60%). Websites had a median DISCERN score of 2.9 (range 2.0–4.5). Websites achieved higher scores on structural criteria (median 3.6 [2.1–4.7]), with 24% rated as “good”. Scores on supporting decision-making questions were lower (2.6 [1.3–4.4]), with only 7% scoring “good”. Conclusion Although numerous breast cancer-related websites exist, most do a poor job providing women with essential information necessary to actively participate in decision-making for breast cancer surgery. Providing easily-accessible, high-quality online information has the potential to significantly improve patients’ experiences with decision-making. PMID:26417898

  8. Developing and validating a practical decision support tool (DST) for biomass selection on marginal land.

    PubMed

    Andersson-Sköld, Y; Bardos, P; Chalot, M; Bert, V; Crutu, G; Phanthavongsa, P; Delplanque, M; Track, T; Cundy, A B

    2014-12-01

    Marginal, often contaminated, sites exist in large areas across the world as a result of historic activities such as industry, transportation and mineral extraction. Remediation, or other improvements, of these sites is typically only considered for sites with high exploitation pressure and those posing the highest risks to human health or the environment. At the same time there is increasing competition for land resources for different needs such as biofuel production. Potentially some of this land requirement could be met by production of biomass on brownfield or other marginal land, thereby improving the land while applying the crop cultivation as part of an integrated management strategy. The design and decision making for such a strategy will be site specific. A decision support framework, the Rejuvenate DST (decision support tool) has been developed with the aim of supporting such site specific decision making. This tool is presented here, and has been tested by applying it to a number of case study sites. The consequent SWOT (strength, weakness, opportunities and threats) analysis is discussed and evaluated. The DST was found to be systematic, transparent, and applicable for diverse sites in France, Romania and Sweden, in addition to the sites to which it was applied through its development. The DST is regarded as especially useful if applied as a checklist in an iterative way throughout the decision process, from identifying potential crops to identifying knowledge gaps, working/non-working management strategies and potential risks. The DST also provides a structure promoting effective stakeholder engagement. PMID:25014888

  9. Determining location and size of medical departments in a hospital network: a multiobjective decision support approach.

    PubMed

    Stummer, Christian; Doerner, Karl; Focke, Axel; Heidenberger, Kurt

    2004-02-01

    Decisions on the location and size of medical departments in a given hospital network are prime examples of priority setting in health care, which is an issue of growing political importance. As such decisions are regularly characterized by multiple and often conflicting objectives in real-life, this paper integrates the fields of hospital planning and multiobjective decision support. The proposed two-phase solution procedure for our corresponding mathematical programming model does not require a priori preference information. Instead, it seeks efficient solutions by means of multiobjective tabu search in the first phase, while applying clustering in the second phase to allow the decision makers to interactively explore the solution space until the "best" configuration is determined. The real-world applicability of our approach is illustrated through a numerical example based on hospital data from Germany. PMID:14977095

  10. Breast cancer therapy planning - a novel support concept for a sequential decision making problem.

    PubMed

    Scherrer, Alexander; Schwidde, Ilka; Dinges, Andreas; Rüdiger, Patrick; Kümmel, Sherko; Küfer, Karl-Heinz

    2015-09-01

    Breast cancer is the most common carcinosis with the largest number of mortalities in women. Its therapy comprises a wide spectrum of different treatment modalities a breast oncologist decides about for the individual patient case. These decisions happen according to medical guide lines, current scientific publications and experiences acquired in former cases. Clinical decision making therefore involves the time-consuming search for possible therapy options and their thorough testing for applicability to the current patient case.This research work addresses breast cancer therapy planning as a multi-criteria sequential decision making problem. The approach is based on a data model for patient cases with therapy descriptions and a mathematical notion for therapeutic relevance of medical information. This formulation allows for a novel decision support concept, which targets at eliminating observed weaknesses in clinical routine of breast cancer therapy planning. PMID:25315184

  11. A Decision Making Methodology in Support of the Business Rules Lifecycle

    NASA Technical Reports Server (NTRS)

    Wild, Christopher; Rosca, Daniela

    1998-01-01

    The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.

  12. [DECIDE: developing and evaluating communication strategies to support informed decisions and practice based on evidence].

    PubMed

    Parmelli, Elena; Amato, Laura; Saitto, Carlo; Davoli, Marina

    2013-10-01

    Healthcare systems are offered with a wide range of technologies and services, but they have to cope with decreasing resources and the uncertainty about what is effective and more appropriate. Making decisions about health care interventions is complex. Decisions should be informed by the best available evidence, being comprehensive to take into account all the relevant aspects (e.g. efficacy, safety, equity, costs), and taken within a limited time period. DECIDE is a project funded by the European Community that, using the GRADE methodology, aims at implementing strategies to enhance dissemination and communication of scientific evidence to support on-time evidence-based decision making in clinical practice and healthcare policies. Communication strategies are developed in order to address different target audiences, trying to meet their information needs. One key target are policy makers and managers who are responsible for coverage decision making. PMID:24326703

  13. Ecosystem services: Challenges and opportunities for hydrologic modeling to support decision making

    NASA Astrophysics Data System (ADS)

    Guswa, Andrew J.; Brauman, Kate A.; Brown, Casey; Hamel, Perrine; Keeler, Bonnie L.; Sayre, Susan Stratton

    2014-05-01

    Ecosystem characteristics and processes provide significant value to human health and well-being, and there is growing interest in quantifying those values. Of particular interest are water-related ecosystem services and the incorporation of their value into local and regional decision making. This presents multiple challenges and opportunities to the hydrologic-modeling community. To motivate advances in water-resources research, we first present three common decision contexts that draw upon an ecosystem-service framework: scenario analysis, payments for watershed services, and spatial planning. Within these contexts, we highlight the particular challenges to hydrologic modeling, and then present a set of opportunities that arise from ecosystem-service decisions. The paper concludes with a set of recommendations regarding how we can prioritize our work to support decisions based on ecosystem-service valuation.

  14. Toward a multi-objective decision support framework to support regulations of unconventional oil and gas development

    NASA Astrophysics Data System (ADS)

    Alongi, M.; Howard, C.; Kasprzyk, J. R.; Ryan, J. N.

    2015-12-01

    Unconventional oil and gas development (UOGD) using hydraulic fracturing and horizontal drilling has recently fostered an unprecedented acceleration in energy development. Regulations seek to protect environmental quality of areas surrounding UOGD, while maintaining economic benefits. One such regulation is a setback distance, which dictates the minimum proximity between an oil and gas well and an object such as a residential or commercial building, property line, or water source. In general, most setback regulations have been strongly politically motivated without a clear scientific basis for understanding the relationship between the setback distance and various performance outcomes. This presentation discusses a new decision support framework for setback regulations, as part of a large NSF-funded sustainability research network (SRN) on UOGD. The goal of the decision support framework is to integrate a wide array of scientific information from the SRN into a coherent framework that can help inform policy regarding UOGD. The decision support framework employs multiobjective evolutionary algorithm (MOEA) optimization coupled with simulation models of air quality and other performance-based outcomes on UOGD. The result of the MOEA optimization runs are quantitative tradeoff curves among different objectives. For example, one such curve could demonstrate air pollution concentrations versus estimates of energy development profits, for different levels of setback distance. Our results will also inform policy-relevant discussions surrounding UOGD such as comparing single- and multi-well pads, as well as regulations on the density of well development over a spatial area.

  15. A Legal Framework to Enable Sharing of Clinical Decision Support Knowledge and Services across Institutional Boundaries

    PubMed Central

    Hongsermeier, Tonya; Maviglia, Saverio; Tsurikova, Lana; Bogaty, Dan; Rocha, Roberto A.; Goldberg, Howard; Meltzer, Seth; Middleton, Blackford

    2011-01-01

    The goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology at scale – across multiple ambulatory care settings and Electronic Health Record technology platforms. In the course of the CDSC research effort, it became evident that a sound legal foundation was required for knowledge sharing and clinical decision support services in order to address data sharing, intellectual property, accountability, and liability concerns. This paper outlines the framework utilized for developing agreements in support of sharing, accessing, and publishing content via the CDSC Knowledge Management Portal as well as an agreement in support of deployment and consumption of CDSC developed web services in the context of a research project under IRB oversight. PMID:22195151

  16. Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes

    PubMed Central

    Rigla, Mercedes; Martínez-Sarriegui, Iñaki; Shalom, Erez; Peleg, Mor; Broens, Tom; Pons, Belén; Caballero-Ruíz, Estefanía; Gómez, Enrique J.; Hernando, M. Elena

    2014-01-01

    The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients’ self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient’s access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients’ personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients’ acceptance of the whole system. PMID:24876573

  17. Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes.

    PubMed

    García-Sáez, Gema; Rigla, Mercedes; Martínez-Sarriegui, Iñaki; Shalom, Erez; Peleg, Mor; Broens, Tom; Pons, Belén; Caballero-Ruíz, Estefanía; Gómez, Enrique J; Hernando, M Elena

    2014-03-01

    The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system. PMID:24876573

  18. Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

    PubMed Central

    2014-01-01

    Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health

  19. Data Mashups: Potential Contribution to Decision Support on Climate Change and Health

    PubMed Central

    Fleming, Lora E.; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E.; Depledge, Michael H.; Sarran, Christophe; Osborne, Nicholas J.; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel

    2014-01-01

    Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on “data mashups”. These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers. PMID:24499879

  20. Data mashups: potential contribution to decision support on climate change and health.

    PubMed

    Fleming, Lora E; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E; Depledge, Michael H; Sarran, Christophe; Osborne, Nicholas J; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel

    2014-02-01

    Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on "data mashups". These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers. PMID:24499879