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<p>Artificial intelligence (AI) is delivering value across all aspects of clinical practice. However, bias may exacerbate healthcare disparities. This review examines the origins of bias in healthcare AI, strategies for mitigation, and responsibilities of relevant stakeholders towards achieving fair and equitable use. We highlight the importance of systematically identifying bias and engaging relevant mitigation activities throughout the AI model lifecycle, from model conception through to deployment and longitudinal surveillance.</p>

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Bias recognition and mitigation strategies in artificial intelligence healthcare applications

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月11日

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  • Fereshteh Hasanzadeh,
  • Colin B. Josephson,
  • Gabriella Waters,
  • Demilade Adedinsewo,
  • Zahra Azizi,
  • James A. White

摘要

Artificial intelligence (AI) is delivering value across all aspects of clinical practice. However, bias may exacerbate healthcare disparities. This review examines the origins of bias in healthcare AI, strategies for mitigation, and responsibilities of relevant stakeholders towards achieving fair and equitable use. We highlight the importance of systematically identifying bias and engaging relevant mitigation activities throughout the AI model lifecycle, from model conception through to deployment and longitudinal surveillance.