Machine Learning and Health Care: Potential Benefits and Issues.
Machine Learning and Health Care: Potential Benefits and Issues.
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机器学习和医疗保健：潜在的好处和问题。
DOI：
10.1097/jac.0000000000000453
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Atkinson,ElizabethG
中科院分区：
文献类型：
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作者：
Atkinson,JGraham;Atkinson,ElizabethG
我们讨论了机器学习（ML）和人工智能（AI）改善医疗保健的潜力，同时详细说明了确保公正和公平实施的注意事项和重要考虑因素。如果用于训练ML算法的数据中存在差异，则必须识别和解释这些差异，这样它们就不会影响性能准确性，也不会被算法解释为缺乏需求。我们特别关注数据构成偏差特别显著的一个领域，即在大型遗传数据库中，因为欧洲血统的人在现有资源中被大大高估了。
We discuss the potential for machine learning (ML) and artificial intelligence (AI) to improve health care, while detailing caveats and important considerations to ensure unbiased and equitable implementation. If disparities exist in the data used to train ML algorithms, they must be recognized and accounted for, so they do not bias performance accuracy or are not interpreted by the algorithm as simply a lack of need. We pay particular attention to an area in which bias in data composition is particularly striking, that is in large-scale genetics databases, as people of European descent are vastly overrepresented in the existing resources.