Chief Medical Officer, Life North America, PartnerRe Reinsurance.
Editor-in-Chief, Journal of Insurance Medicine.
J Insur Med. 2024 Jul 1;51(2):64-76. doi: 10.17849/insm-51-2-64-76.1.
Recent artificial intelligence (AI) advancements in cardiovascular medicine offer potential enhancements in diagnosis, prediction, treatment, and outcomes. This article aims to provide a basic understanding of AI enabled ECG technology. Specific conditions and findings will be discussed, followed by reviewing associated terminology and methodology. In the appendix, definitions of AUC versus accuracy are explained. The application of deep learning models enables detecting diseases from normal electrocardiograms at accuracy not previously achieved by technology or human experts. Results with AI enabled ECG are encouraging as they considerably exceeded current screening models for specific conditions (i.e., atrial fibrillation, left ventricular dysfunction, aortic stenosis, and hypertrophic cardiomyopathy). This could potentially lead to a revitalization of the utilization of the ECG in the insurance domain. While we are embracing the findings with this rapidly evolving technology, but cautious optimism is still necessary at this point.
最近心血管医学领域的人工智能 (AI) 进展为诊断、预测、治疗和预后提供了潜在的增强。本文旨在提供对 AI 赋能心电图技术的基本理解。将讨论特定的情况和发现，然后回顾相关的术语和方法。在附录中，解释了 AUC 与准确性的定义。深度学习模型的应用使得从正常心电图中检测疾病的准确性达到了以前技术或人类专家无法达到的水平。AI 赋能心电图的结果令人鼓舞，因为它们大大超过了特定情况下（即心房颤动、左心室功能障碍、主动脉瓣狭窄和肥厚型心肌病）的现有筛查模型。这可能会导致心电图在保险领域的利用率重新得到重视。虽然我们对这项快速发展的技术的发现感到兴奋，但在这一点上仍然需要谨慎乐观。
