人工智能范式中的心血管疾病的多基因风险评分:一篇评论
Narendra N Khanna1,2, Manasvi Singh3,4, Mahesh Maindarkar2,3,5
1Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi, India.
Journal of Korean medical science
|November 28, 2023
概括
基于人工智能 (AI) 的多基因风险评分 (PRS) 在预测心血管疾病 (CVD) 风险方面比传统方法更准确. 人工智能模型整合了更多的遗传和环境因素,以准确,个性化的心血管疾病风险评估和管理.
科学领域:
- 基因组学就是基因组学.
- 心血管医学 心血管医学
- 人工智能的人工智能
背景情况:
- 心血管疾病 (CVD) 构成了重大的社会负担.
- 在心血管疾病风险中的遗传倾向和环境因素之间的相互作用尚未完全理解.
- 多基因风险评分 (PRS) 是评估对心血管疾病等复杂疾病的遗传敏感性的新兴工具.
研究的目的:
- 审查和比较基于人工智能 (AI) 的PRS模型与用于预测心血管疾病风险的传统方法.
- 评估AI在提高心血管疾病风险评估的准确性和个性化方面的潜力.
- 通过整合不同的数据类型和减少维度,提出关于AI在改善心血管疾病风险预测方面的作用的假设.
主要方法:
- 使用PRISMA搜索方法进行系统的文献审查.
- 分析和比较传统的PRS计算器与基于AI的PRS模型.
- 评估AI结合多种遗传和非遗传风险因素的能力.
主要成果:
- 基于AI的PRS模型在预测心血管疾病风险方面表现优于传统的PRS计算器.
- 人工智能有助于整合更广泛的遗传和非遗传因素,以更精确地估计风险.
- 人工智能方法有效地减少了大型基因组数据集的维度,提高了模型的准确性和效率.
结论:
- 基于人工智能的PRS为心血管疾病风险预测提供了更准确和个性化的方法.
- 人工智能在PRS开发中的整合对个性化心血管疾病预防和治疗策略有重大影响.
- 人工智能通过利用全面的遗传和环境数据来增强PRS的预测能力.
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