An objective framework for evaluating unrecognized bias in medical AI models predicting COVID-19 outcomes

OBJECTIVE: The increasing translation of artificial intelligence (AI)/machine learning (ML) models into clinical practice brings an increased risk of direct harm from modeling bias; however, bias remains incompletely measured in many medical AI applications. This article aims to provide a framework...

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Detalles Bibliográficos
Autores principales: Estiri, Hossein, Strasser, Zachary H, Rashidian, Sina, Klann, Jeffrey G, Wagholikar, Kavishwar B, McCoy, Thomas H, Murphy, Shawn N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277645/
https://www.ncbi.nlm.nih.gov/pubmed/35511151
http://dx.doi.org/10.1093/jamia/ocac070

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277645/
https://www.ncbi.nlm.nih.gov/pubmed/35511151
http://dx.doi.org/10.1093/jamia/ocac070

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