人工智能和网络医学:通往精准医学的道路
Lucia Altucci1, Lina Badimon2, Jean-Luc Balligand3
1Department of Precision Medicine, University of Campania Luigi Vanvitelli, Naples, Italy.
NEJM AI
|September 8, 2025
概括
网络医学 (NM) 和人工智能 (AI) 的整合加速了精准医学的发现. 将这些方法结合起来,可以加强对多原子数据的分析,以便更好地了解疾病和针对性治疗.
科学领域:
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 20多年来,网络医学 (NM) 已在疾病机制阐明,药物向识别和精确疗法开发方面取得了先进.
- 人工智能 (AI),特别是深度学习与NM的整合是一个具有显著治疗潜力的增长领域.
研究的目的:
- 审查AI和NM的联合使用,以推进精准医学.
- 为了说明整合AI和NM在分析复杂的生物医学数据中的成功和挑战.
主要方法:
- 关于人工智能和NM集成的当前文献的综述.
- 使用结合AI和NM方法分析多原子数据集.
- 在网络医学框架内探索深度学习技术.
主要成果:
- 人工智能和NM的协同作用提高了计算分析的速度和预测精度.
- 结合方法可以从大型多原子数据集中获得更深入的生物学见解.
- 成功的应用表明了阐明复杂疾病机制的潜力.
结论:
- 人工智能和NM的整合为精准医学提供了一个强大的计算策略.
- 这种综合方法对于导航复杂的多原子数据至关重要.
- 人工智能与NM集成的持续挑战需要进一步的研究和开发.
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