Optimal testing policies for diagnosing patients with intermediary probability of disease

Fernandes De Arruda, Edilson, Pereira, Basílio B., Thiers, Clarissa A. and Tura, Bernardo R. 2019. Optimal testing policies for diagnosing patients with intermediary probability of disease. Artificial Intelligence in Medicine 97 , pp. 89-97. 10.1016/j.artmed.2018.11.005

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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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Publisher:	Elsevier
ISSN:	0933-3657
Date of First Compliant Deposit:	6 January 2020
Date of Acceptance:	17 November 2018
Last Modified:	20 Nov 2024 19:00
URI:	https://orca.cardiff.ac.uk/id/eprint/128226

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