Comprendre l’équité en santé grâce à l’intelligence artificielle. L’exemple de l’Agent-Based Modelling (ABM) [Understanding health equity through artificial intelligence The case of Agent-Based Modelling (ABM)]

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Etat: Public
Version: Final published version
Licence: CC BY-NC-ND 4.0
ID Serval
serval:BIB_ED2378231FFB
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Etude de cas (case report): rapporte une observation et la commente brièvement.
Collection
Publications
Institution
Titre
Comprendre l’équité en santé grâce à l’intelligence artificielle. L’exemple de l’Agent-Based Modelling (ABM) [Understanding health equity through artificial intelligence The case of Agent-Based Modelling (ABM)]
Périodique
Revue medicale suisse
Auteur⸱e⸱s
Morisod K., Nguyen K., Grazioli V.S., Marti J., Bodenmann P.
ISSN
1660-9379 (Print)
ISSN-L
1660-9379
Statut éditorial
Publié
Date de publication
05/07/2023
Peer-reviewed
Oui
Volume
19
Numéro
834
Pages
1322-1326
Langue
français
Notes
Publication types: English Abstract ; Journal Article
Publication Status: ppublish
Résumé
Agent-Based Modelling (ABM) is a computer modelling technique that simulates the behaviour and interactions of autonomous agents within a virtual environment. Applied to health equity, this technique allows for a better understanding of the complex social and economic determinants that contribute to health inequities and enables the evaluation of the potential effects of public policies on the latter. Despite some limitations related to the accessibility and quality of health data and the complexity of the models, ABM appears to be a promising tool in the field of health equity, both for researchers in public or community health and for policy makers.
Mots-clé
Humans, Health Equity, Artificial Intelligence, Public Policy, Public Health, Systems Analysis, Health Policy
Pubmed
Création de la notice
07/07/2023 10:57
Dernière modification de la notice
19/08/2023 7:16
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