Department of Medicine, Montréal Heart Institute, Université de Montréal, Montréal, Québec, Canada.
Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, Massachusetts, USA.
Can J Cardiol. 2024 Oct;40(10):1813-1827. doi: 10.1016/j.cjca.2024.06.011. Epub 2024 Jun 18.
This article reviews the application of artificial intelligence (AI) in acute cardiac care, highlighting its potential to transform patient outcomes in the face of the global burden of cardiovascular diseases. It explores how AI algorithms can rapidly and accurately process data for the prediction and diagnosis of acute cardiac conditions. The review examines AI's impact on patient health across various diagnostic tools such as echocardiography, electrocardiography, coronary angiography, cardiac computed tomography, and magnetic resonance imaging, discusses the regulatory landscape for AI in health care, and categorises AI algorithms by their risk levels. Furthermore, it addresses the challenges of data quality, generalisability, bias, transparency, and regulatory considerations, underscoring the necessity for inclusive data and robust validation processes. The review concludes with future perspectives on integrating AI into clinical workflows and the ongoing need for research, regulation, and innovation to harness AI's full potential in improving acute cardiac care.
这篇文章综述了人工智能(AI)在急性心脏护理中的应用,强调了其在面对全球心血管疾病负担时改变患者预后的潜力。它探讨了 AI 算法如何快速准确地处理数据,以预测和诊断急性心脏状况。该综述考察了 AI 在各种诊断工具(如超声心动图、心电图、冠状动脉造影、心脏计算机断层扫描和磁共振成像)中的应用对患者健康的影响,讨论了 AI 在医疗保健中的监管格局,并按风险级别对 AI 算法进行了分类。此外,它还解决了数据质量、通用性、偏差、透明度和监管考虑等方面的挑战,强调了包容性数据和强大的验证过程的必要性。该综述最后对将 AI 整合到临床工作流程中的未来展望以及在利用 AI 提高急性心脏护理水平方面持续进行研究、监管和创新的必要性进行了总结。