数字心血管双胞胎,人工智能代理人和传感器数据:从系统架构到主动心脏健康的叙事审查
Nurdaulet Tasmurzayev1,2, Bibars Amangeldy1,2, Baglan Imanbek1
1Faculty of Information Technology, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
创新的数字心血管双胞胎集成可穿戴传感器和人工智能,提前几周预测无声心脏病,将心脏病学转向主动,个性化预防.
科学领域:
- 心血管医学和数字健康.
- 医疗保健中的人工智能.
- 生物医学工程和传感器技术.
背景情况:
- 心血管疾病 (CVD) 是导致死亡的首要原因,目前的治疗方法往往是反应性的,只有在显著的组织损伤后才能进行干预.
- 现有的缺血,心律失常和重塑的诊断方法是偶发的,并迟迟发现病理,限制治疗效果.
- 在心脏病学中,持续,预测性监测的需要对于向预防性护理转变至关重要.
研究的目的:
- 审查心血管疾病 (CVD) 的创新诊断技术.
- 检查数字心血管双胞胎,人工智能 (AI) 和预测性心脏病学的多模式数据流的整合.
- 探索人工智能驱动系统在早期检测和个性化预防心血管疾病方面的潜力.
主要方法:
- 从主要科学数据库 (PubMed,Scopus等) 中对183项研究 (2016-2025) 的叙述性综述. ) 的情况.
- 数字心血管双胞胎架构的分析,包括可穿戴物联网设备 (ECG,PPG),临床记录,生物标志物和遗传标志物的数据.
- 检查人工智能技术,包括机器学习,深度学习,图形/变压器网络,生成人工智能,医疗LLM以及用于数据解释和决策支持的自主代理.
主要成果:
- 数字心血管双胞胎,由人工智能和多模式数据提供动力,可以在临床表现前几周早期检测无声病理.
- 由传感器,混合分析,人工智能驱动的决策支持和前性模拟组成的四层架构可促进持续监控和可操作的建议.
- 血液动力学模型与先进的人工智能技术的整合有效地管理不确定性,并为个性化干预创建预后模型.
结论:
- 这种多层次的方法将持续的心血管数据转化为可操作的见解,使预测和预防性护理成为可能.
- 开发的框架支持创建软件作为医疗设备生态系统,并为心血管医学中可靠的人工智能提供监管指导.
- 从反应性治疗转向主动,个性化的预防,对降低心血管死亡率具有重大前景.
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