Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals. - Université de Lille
Article Dans Une Revue Studies in Health Technology and Informatics Année : 2024

Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.

Résumé

The health product circuit corresponds to the chain of steps that a medicine goes through in hospital, from prescription to administration. The safety and regulation of all the stages of this circuit are major issues to ensure the safety and protect the well-being of hospitalized patients. In this paper we present an automatic system for analyzing prescriptions using Artificial Intelligence (AI) and Machine Learning (ML), with the aim of ensuring patient safety by limiting the risk of prescription errors or drug iatrogeny. Our study is made in collaboration with Lille University Hospital (LUH). We exploited the MIMIC-III (Medical Information Mart for Intensive Care) a large, single-center database containing information corresponding to patients admitted to critical care units at a large tertiary care hospital.
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Dates et versions

hal-04582831 , version 1 (24-05-2024)

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Sarah Ben Othman, Bertrand Décaudin, Pascal Odou, C. Rousselière, E. Cousein, et al.. Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.. Studies in Health Technology and Informatics, 2024, Studies in Health Technology and Informatics, 310, pp.1593-1597. ⟨10.3233/SHTI231332⟩. ⟨hal-04582831⟩
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