医疗保健中的机器学习：与隐私、可解释性和偏差相关的伦理问题。

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

机构信息

Department of Philosophy, University of North Carolina at Chapel Hill.

Center for Bioethics, University of North Carolina at Chapel Hill.

出版信息

N C Med J. 2024 Jun;85(4):240-245. doi: 10.18043/001c.120562.

DOI:10.18043/001c.120562

PMID:39466090

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.

摘要

机器学习模型在医学应用中具有巨大的潜力，但也带来了一系列伦理挑战。在本次调查中，我们重点关注训练数据、模型可解释性和偏差，以及与隐私、自主性和健康公平性相关的问题。