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Academic machine learning researchers' ethical perspectives on algorithm development for health care: a qualitative study.

Max KasunKatie RyanJodi PaikKyle Lane-McKinleyLaura Bodin DunnLaura Weiss RobertsJane Paik Kim
Published in: Journal of the American Medical Informatics Association : JAMIA (2023)
Participants described key areas where increased support for ethics may be needed; technical challenges affecting clinical acceptability; and standards related to scientific integrity, beneficence, and justice that may be higher in medicine compared to other industries engaged in ML innovation. Our results help shed light on the perspectives of ML researchers in medicine regarding the range of ethical issues they encounter or anticipate in their work, including areas where more attention may be needed to support the successful development and integration of medical ML tools.
Keyphrases
  • machine learning
  • healthcare
  • big data
  • deep learning
  • artificial intelligence
  • working memory
  • decision making
  • health insurance
  • health information