The use of machine learning (ML) in health care raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of health care. Specifically, we frame ethics of ML in health care through the lens of social justice. We describe ongoing efforts and outline challenges in a proposed pipeline of ethical ML in health, ranging from problem selection to post-deployment considerations. We close by summarizing recommendations to address these challenges.

Irene Y. Chen

Emma Pierson

Sherri Rose

Shalmali Joshi

Kadija Ferryman

Marzyeh Ghassemi

Annual Review of Biomedical Data Science

Annu. Rev. Biomed. Data Sci.

Ethical Machine Learning in Healthcare

Ethics of ML in healthcare is frame through the lens of social justice, and ongoing efforts and challenges in a proposed pipeline of ethical ML in health, ranging from problem selection to postdeployment considerations are described.

医疗保健中的伦理机器学习

Ethical Machine Learning in Healthcare

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Journal Info

Category	Quartile
MATHEMATICAL & COMPUTATIONAL BIOLOGY	1