在心力衰竭中使用人工智能引导的神经调节:机制,证据和未来方向
Rabiah Aslam Ansari1, Sidhartha Gautam Senapati2, Vibhor Ahluwalia3
1Digital Engineering & Artificial Intelligence Laboratory (DEAL), Department of Critical Care Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
Journal of cardiovascular development and disease
|August 27, 2025
概括
人工智能 (AI) 增强自主神经调节以治疗心力衰竭. 以人工智能为指导的策略改善了患者选择和个性化治疗减少喷射分数 (HFrEF) 和保留喷射分数 (HFpEF) 的心力衰竭.
科学领域:
- 心脏病学
- 生物医学工程
- 人工智能
背景情况:
- 心力衰竭 (HF),包括HFrEF和HFpEF,是全球主要的健康挑战,对HFpEF的有效治疗方法有限.
- 这两种HF类型都导致高重住院率和生活质量下降,特别是在伴随疾病的老年人中.
研究的目的:
- 审查人工智能 (AI) 在促进自主神经调节以改善心力衰竭管理中的作用.
- 探索人工智能在个性化神经调节疗法的潜力.
主要方法:
- 对心力衰竭的自主神经调节中人工智能应用的当前文献的审查.
- 对人工智能在患者选择,刺激策略优化和自适应性闭环系统中的作用进行分析.
- 检查人工智能驱动的HFpEF深度表型和HFrEF的动态刺激调整.
主要成果:
- 人工智能增强了患者选择,并优化了心力衰竭中自主神经调节的刺激策略.
- 人工智能驱动的自适应系统根据HFrEF的生理反动态调整神经调节.
- 人工智能促进了HFpEF的深度表型识别,以确定对神经调节干预反应的患者子组.
结论:
- 人工智能引导的自主神经调节为心力衰竭提供了个性化,数据驱动的治疗策略.
- 应对数据整合,道德监督和临床采用方面的挑战对于HF的真实应用至关重要.
- 跨学科合作和道德创新对于推动以患者为中心的心力衰竭护理至关重要.
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