  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.
