Graduate School of Arts and Sciences, Georgetown University, Washington, District of Columbia, USA.
Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
World J Surg. 2024 Sep;48(9):2073-2089. doi: 10.1002/wjs.12265. Epub 2024 Jul 17.
Artificial intelligence (AI) has emerged as a tool to potentially increase the efficiency and efficacy of cardiovascular care and improve clinical outcomes. This study aims to provide an overview of applications of AI in cardiac surgery.
A systematic literature search on AI applications in cardiac surgery from inception to February 2024 was conducted. Articles were then filtered based on the inclusion and exclusion criteria and the risk of bias was assessed. Key findings were then summarized.
A total of 81 studies were found that reported on AI applications in cardiac surgery. There is a rapid rise in studies since 2020. The most popular machine learning technique was random forest (n = 48), followed by support vector machine (n = 33), logistic regression (n = 32), and eXtreme Gradient Boosting (n = 31). Most of the studies were on adult patients, conducted in China, and involved procedures such as valvular surgery (24.7%), heart transplant (9.4%), coronary revascularization (11.8%), congenital heart disease surgery (3.5%), and aortic dissection repair (2.4%). Regarding evaluation outcomes, 35 studies examined the performance, 26 studies examined clinician outcomes, and 20 studies examined patient outcomes.
AI was mainly used to predict complications following cardiac surgeries and improve clinicians' decision-making by providing better preoperative risk assessment, stratification, and prognostication. While the application of AI in cardiac surgery has greatly progressed in the last decade, further studies need to be conducted to verify accuracy and ensure safety before use in clinical practice.
人工智能（AI）已成为提高心血管护理效率和效果、改善临床结果的潜在工具。本研究旨在概述 AI 在心脏外科中的应用。
对从创建到 2024 年 2 月 AI 在心脏外科中的应用进行了系统的文献检索。然后根据纳入和排除标准以及偏倚风险对文章进行筛选，总结主要发现。
共发现 81 项报告 AI 在心脏外科中应用的研究。自 2020 年以来，研究数量迅速增加。最流行的机器学习技术是随机森林（n=48），其次是支持向量机（n=33）、逻辑回归（n=32）和极端梯度提升（n=31）。大多数研究针对成年患者，在中国进行，涉及瓣膜手术（24.7%）、心脏移植（9.4%）、冠状动脉血运重建（11.8%）、先天性心脏病手术（3.5%）和主动脉夹层修复（2.4%）等手术。关于评估结果，35 项研究检查了性能，26 项研究检查了临床医生的结果，20 项研究检查了患者的结果。
AI 主要用于预测心脏手术后的并发症，并通过提供更好的术前风险评估、分层和预后来改善临床医生的决策。虽然 AI 在心脏外科中的应用在过去十年中取得了很大进展，但在临床实践中使用之前，还需要进一步研究以验证准确性并确保安全性。
