Machine Learning in Health Care: Ethical Considerations Tied to Privacy, Interpretability, and Bias.

Journal: North Carolina medical journal
PMID:

Abstract

Machine learning models hold great promise with medical applications, but also give rise to a series of ethical challenges. In this survey we focus on training data, model interpretability and bias and the related issues tied to privacy, autonomy, and health equity.

Authors

  • Thomas Hofweber
    Department of Philosophy, University of North Carolina at Chapel Hill.
  • Rebecca L Walker
    Center for Bioethics, University of North Carolina at Chapel Hill.