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在免疫疾病中实现健康公平:在不断变化的卫生系统格局中利用大数据和人工智能
Stan Kachnowski1,2, Asif H Khan3, Shadé Floquet4
1Healthcare Innovation and Technology Lab, New York, NY, United States.
Frontiers in big data
|December 1, 2025
概括
不断增加的免疫疾病需要大数据和人工智能 (AI) 来预防和治疗. 解决人工智能和大数据分析 (BDA) 的潜在偏见对于在免疫疾病研究中实现健康公平至关重要.
科学领域:
- 免疫学 免疫学 免疫学
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
背景情况:
- 免疫疾病的日益流行,给全球健康带来了重大挑战.
- 有效的管理需要全面的"大数据",包括分布,人口统计,风险因素,生物标志物和预后.
研究的目的:
- 审查挑战,并提出解决方案,以利用大数据,人工智能 (AI) 和大数据分析 (BDA) 在免疫疾病中实现健康公平.
- 突出解决偏见的重要性,并确保数据驱动健康战略的包容性.
主要方法:
- 文献综述专注于大数据,人工智能和BDA在免疫疾病研究中的应用.
- 分析与数据质量,代表性,偏见和利益相关方参与相关的挑战.
主要成果:
- 关键的挑战包括政治意愿,利益相关者参与,数据质量,少数群体的代表性,以及缓解AI/BDA偏见.
- 解决方案包括通过广泛参与,增强技术能力和实施强有力的公平评估和治理来促进信任.
结论:
- 合作努力和共享协调的大数据的基础设施是必不可少的.
- 有效利用人工智能和BDA需要透明,公平和有影响力的数据驱动解决方案,以促进免疫疾病的健康公平.
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