Optimal testing policies for diagnosing patients with intermediary probability of disease
Optimal testing policies for diagnosing patients with intermediary probability of disease
Data
2019
Autores
Arruda, Edilson F.
Pereira, Basílio B.
Thiers, Clarissa A.
Tura, Bernardo R.
Journal Title
Journal ISSN
Volume Title
Publisher
Artificial Intelligence in Medicine
Resumo
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.
Description
Palavras-chave
Stochastic shortest path, Healthcare problems, Diagnosis
Citação
Arruda 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.