Irene Y Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi
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引用次数: 0
摘要
在医疗保健领域使用机器学习（ML）会引发许多伦理问题，特别是由于模型可能会扩大现有的健康不平等。在此，我们概述了在医疗保健领域推进公平机器学习的伦理考虑因素。具体来说，我们将从社会正义的角度来阐述医疗保健领域的 ML 伦理问题。我们描述了正在进行的努力，并概述了拟议中的健康领域道德人工智能管道所面临的挑战，包括从问题选择到部署后的考虑因素。最后，我们总结了应对这些挑战的建议。
The use of machine learning (ML) in healthcare raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of healthcare. Specifically, we frame ethics of ML in healthcare 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 postdeployment considerations. We close by summarizing recommendations to address these challenges.
期刊介绍：
The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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