探索人工智能对个性化医学的性别偏见:针对跨性别社区成员的焦点小组研究
Nataly Buslón1, Davide Cirillo2, Oriol Rios3,4
1Social and Responsible Computing, Department of Engineering, Universitat Pompeu Fabra, Tànger, 122-140, Barcelona, 08018, Spain, +34 935 42 22 01.
Journal of medical Internet research
|July 29, 2025
概括
人工智能 (AI) 可以改善跨性别社区的个性化医疗,但必须解决数据隐私和算法偏见等挑战. 社区参与和跨特定数据是开发包容性AI健康解决方案的关键.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 精准医学是一门精准的医学.
背景情况:
- 使用人工智能的个性化医学进步往往忽视了跨性别社区.
- 根据独特的跨性别健康需求量身定制AI健康解决方案的研究不足.
- 确保精准医学的包容性需要解决这个人口差距.
研究的目的:
- 识别跨个性化医学中人工智能的挑战和解决方案.
- 促进跨包容,多学科的方法.
- 强调文化能力和社区参与AI医疗保健的重要性.
主要方法:
- 具有最终用户和利益相关方参与的沟通方法.
- 与跨界社区代表进行反复商.
- 三个焦点小组,包括16名跨性别成年人,讨论精准医学中的AI.
主要成果:
- 障碍包括数据隐私问题,算法偏见和缺乏跨特定健康数据.
- 参与者担心由于cisnormative数据模型的错误诊断.
- 人工智能有机会通过社区主导的数据和透明度来改善结果.
结论:
- 一种跨包容性AI方法对于个性化医疗至关重要.
- 通过社区驱动的解决方案来应对挑战,可以弥合健康差距.
- 包容性AI设计对于边缘化社区的公平健康创新至关重要.
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