基于心电图的人工智能用于检测低射出分数:当代审查
Hadrian Hoang-Vu Tran1, Audrey Thu2, Axel Fuertes1
1From the Department of Internal Medicine, Hackensack University Medical Center-Palisades Medical Center, North Bergen, NJ.
Cardiology in review
|June 23, 2025
概括
人工智能 (AI) 正在彻底改变心电图 (ECG) 的心血管护理. AI-ECG应用程序可以提高疾病检测,风险评估和治疗,为改善患者结果铺平道路.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 越来越多地融入医疗保健,特别是在心血管诊断方面.
- 电心电图 (ECG) 是心血管评估的基石,但它的诊断能力正在被AI显著增强.
- 最近的进展集中在AI-ECG应用中,用于早期疾病检测,风险分层和治疗优化.
研究的目的:
- 审查人工智能增强心电图 (AI-ECG) 的最新技术创新和临床整合策略.
- 突出新兴的人工智能方法及其对ECG分析的影响.
- 讨论AI-ECG技术在现实世界中采用的基本步骤.
主要方法:
- 审查关于人工智能在心电图分析中的应用的当前文献.
- 探索深度学习模型,从心电图数据中检测各种心血管和全身疾病.
- 讨论多式模式学习,联合方法和AI-ECG强度的时间建模.
主要成果:
- 深度学习模型在使用心电图识别结构性心脏病,心律失常和系统性疾病方面表现有前途.
- 强调对模型可解释性,公平性和使用各种数据集的概括性的关键需求.
- 新兴的策略,如多模式和联合学习,旨在提高AI-ECG的稳定性和临床相关性.
结论:
- AI-ECG对心血管保健具有变革性的潜力,可以改善诊断和患者管理.
- 成功的临床整合需要解决模型可解释性,公平性和多样化的数据表示.
- 现实世界的采用需要前性验证,监管清晰度和道德考虑,以实现公平的部署.
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