Machine Learning in Health Care: Ethical Considerations Tied to Privacy, Interpretability, and Bias
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
- Rebecca L. Walker (ORCID: https://orcid.org/0000-0003-3789-3992)
- Thomas Hofweber (ORCID: https://orcid.org/0000-0001-7095-6559)
Institutions
- University of North Carolina at Chapel Hill (US)
Publication Details
- Journal
- UNC Libraries
- Published
- 2024-10-05
- DOI
- https://doi.org/10.17615/8yj9-8f53
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00