Literature DB >> 30528359

Optimal testing policies for diagnosing patients with intermediary probability of disease.

Edilson F Arruda1, Basílio B Pereira2, Clarissa A Thiers3, Bernardo R Tura4.   

Abstract

This 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.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Diagnosis; Healthcare problems; Stochastic shortest path

Mesh:

Year:  2018        PMID: 30528359     DOI: 10.1016/j.artmed.2018.11.005

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  2 in total

1.  Resource optimization for cancer pathways with aggregate diagnostic demand: a perishable inventory approach.

Authors:  Edilson F Arruda; Paul Harper; Tracey England; Daniel Gartner; Emma Aspland; Fabrício O Ourique; Tom Crosby
Journal:  IMA J Manag Math       Date:  2020-06-30       Impact factor: 1.186

2.  Diagnostic Policies Optimization for Chronic Diseases Based on POMDP Model.

Authors:  Wenqian Zhang; Haiyan Wang
Journal:  Healthcare (Basel)       Date:  2022-02-01
  2 in total

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