Optimal testing policies for diagnosing patients with intermediary probability of disease

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dc.contributor.authorArruda, Edilson F.
dc.contributor.authorPereira, Basílio B.
dc.contributor.authorThiers, Clarissa A.
dc.contributor.authorTura, Bernardo R.
dc.date.accessioned2023-12-06T17:10:22Z
dc.date.available2023-12-06T17:10:22Z
dc.date.issued2019
dc.description.abstractThis paper proposes a stochastic shortest path approach to find an optimal sequence of tests to confirm or discard a disease, for any prescribed optimality criterion. The idea is to select the best sequence in which to apply a series of available tests, with a view at reaching a diagnosis with minimum expenditure of resources. The proposed approach derives an optimal policy whereby the decision maker is provided with a test strategy for each a priori probability of disease, aiming to reach posterior probabilities that warrant either immediate treatment or a not-ill diagnosis.
dc.identifier.citationArruda EF, Pereira BB, Thiers CA, Tura BR. Optimal testing policies for diagnosing patients with intermediary probability of disease. Artif Intell Med. 2019 Jun;97:89-97. doi: 10.1016/j.artmed.2018.11.005. Epub 2018 Dec 5. PMID: 30528359.
dc.identifier.otherDOI: 10.1016/j.artmed.2018.11.005
dc.identifier.urihttps://dspace.inc.saude.gov.br/handle/123456789/375
dc.language.isoen
dc.publisherArtificial Intelligence in Medicine
dc.subjectStochastic shortest pathen
dc.subjectHealthcare problemsen
dc.subjectDiagnosisen
dc.subject.meshStochastic Processesen
dc.subject.meshProbabilityen
dc.subject.meshHumansen
dc.subject.meshDiagnosisen
dc.subject.meshBayes Theoremen
dc.subject.meshAlgorithmsen
dc.titleOptimal testing policies for diagnosing patients with intermediary probability of disease
dc.typeArticle
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