Intelligent Decision Support in Medicine: back to Bayes?

dc.creatorLindgaard,Gitte
dc.creatorPyper,Catherine
dc.creatorFrize,Monique
dc.creatorWalker,Robin
dc.creatorBoutilier,Craig
dc.creatorHui,Bowen
dc.creatorNarasimhan,Sheila
dc.creatorFolkens,Janette
dc.creatorWinogron,Bill
dc.creatorEgan,Peter
dc.creatorJones,Colin
dc.date2008
dc.date.accessioned2024-02-06T12:56:56Z
dc.date.available2024-02-06T12:56:56Z
dc.descriptionDecision Support Systems are proliferating rapidly in many areas of human endeavour including clinical medicine and psychology. While these are typically based on rule-based systems, decision trees, or Artificial Neural Networks, this paper argues that Bayes Theorem can be applied fruitfully to support expert decisions both in dynamically changing situations requiring the system progressively to adapt, and when this is not the case. One example of each of these two types is given. One provides diagnostic support for human decision makers; the other, an e-health mental intervention system provides decision rules enabling it to respond and provide the most appropriate training modules to input from clients with changing needs. The contributions of psychological research underlying both systems is summarized.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-014-16-2720
dc.identifierhttps://lib.jucs.org/article/29182/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/9865
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 14(16): 2720-2736
dc.subjectBayes' Theorem
dc.subjectDecision Support Systems (DSS)
dc.subjectdiagnostic error
dc.subjectindividuating information
dc.subjectbase rates
dc.subjecte-health intervention
dc.titleIntelligent Decision Support in Medicine: back to Bayes?
dc.typeResearch Article
Файлы