系统人类免疫学和人工智能:免疫设定点和免疫健康
Yona Lei1, John S Tsang1,2,3
1Yale Center for Systems and Engineering Immunology and Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA;
Annual review of immunology
|April 25, 2025
概括
人工智能 (AI) 和机器学习 (ML) 分析复杂的免疫数据,以预测个人健康结果和个性化干预措施. 这些工具揭示了免疫变异的模式,以更好地检测疾病和健康策略.
科学领域:
- 系统免疫学 系统免疫学
- 计算生物学是一种计算生物学.
- 免疫学 免疫学 免疫学
背景情况:
- 免疫系统对健康至关重要,防御病原体并维持平衡.
- 免疫系统表现出显著的个体和人口变异性.
- 系统人类免疫学的进步将免疫状态与疾病易感性和干预反应联系起来.
研究的目的:
- 审查了解人类免疫变异和预测健康结果的进展.
- 探索人工智能 (AI),特别是机器学习 (ML) 在系统免疫学中的应用.
- 突出AI在个性化健康策略和早期疾病检测方面的潜力.
主要方法:
- 关于系统人类免疫学和人工智能应用的最新文献的审查.
- 讨论机器学习建模方法在分析复杂的免疫数据.
- 探索人工智能驱动的预测模型和免疫状态嵌入.
主要成果:
- 人工智能和机器学习揭示了大规模免疫数据中隐藏的模式.
- 预测模型可以预测个体免疫反应和干预结果.
- 免疫设定点和免疫健康等概念提供了对整体幸福感的见解.
结论:
- 人工智能在开发个性化健康策略方面具有重大潜力.
- 人工智能可以实现早期疾病检测和预测干预反应.
- 免疫系统是监测和测量健康状况的宝贵窗口.
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