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Updated: Sep 9, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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在医疗保健数据集中检测,描述和缓解隐含和明确的种族偏见:算法开发和验证研究

Faris Gulamali1, Ashwin Shreekant Sawant1, Lora Liharska1

  • 1Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY, 10029, United States, 1 2122416500.

Journal of medical Internet research
|September 4, 2025
PubMed
概括

通过指导数据收集和重新标记, 一种名为AEquity的新指标有效地减少了医疗数据中的算法偏差. 这种方法在各种数据集和算法中表现优于现有方法,提高了人工智能诊断的公平性.

关键词:
偏见以数据为中心的人工智能公平性机器学习

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