超越性别数据差距:共同创建公平的数字患者双胞胎
Nora Weinberger1, Daniela Hery2, Dana Mahr1
1Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
Frontiers in digital health
|May 15, 2025
概括
数字患者双胞胎可以个性化医疗,但往往缺乏性别和社会经济数据,导致健康差异. 包容性设计对于医疗保健中的公平人工智能至关重要.
科学领域:
- 数字健康数字健康
- 人工智能的人工智能
- 个性化医疗是个性化的医疗.
背景情况:
- 数字患者双胞胎将患者数据与人工智能集成,用于个性化诊断和治疗.
- 目前的数字患者双胞胎经常忽视性别和社会经济因素,造成健康结果差异.
- 这种数据缺口是数字健康领域的一个公认问题,影响了临床有效性.
研究的目的:
- 探索数字患者双胞胎的跨学科方面,包括技术,医学,社会和道德方面的挑战.
- 强调在开发数字患者双胞胎时需要性别敏感的设计和共同创作.
- 突出创造更具包容性和道德责任的数字患者双胞胎的战略.
主要方法:
- 跨学科连接的迷你回顾.
- 探索技术基础,医学相关性以及社会/道德挑战.
- 对性别敏感的设计和共同创作方法的分析.
主要成果:
- 数字患者双胞胎在没有交叉和包容性框架的情况下,可能会延续不平等.
- 性别,人工智能驱动的决策和健康平等之间的相互作用至关重要.
- 目前的方法可能会强化现有的偏见,减少临床效用.
结论:
- 包容性和道德责任的数字患者双胞胎需要解决性别数据差距.
- 共同创造和交叉框架对于减轻健康差异至关重要.
- 需要进一步的跨学科方法来确保在个性化医学中公平的AI.
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