标题： 用于冠内光学相干断层扫描分析的人工智能的审查与建议 显示英文标题

标题： Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis

摘要： 人工智能（AI）方法在从血管内光学相干断层扫描（IVOCT）图像中快速准确诊断冠状动脉疾病（CAD）方面具有巨大潜力。 大量论文已发表，描述了用于不同诊断任务的基于AI的模型，但目前尚不清楚哪些模型具有潜在的临床应用价值并得到了适当的验证。 本系统综述考虑了2015年1月至2023年2月期间发表的关于使用IVOCT进行CAD基于AI诊断的文献。 我们的搜索确定了5,576项研究，经过初步筛选后纳入513项，经过质量筛选后最终纳入系统综述的有35项研究。 我们的研究结果表明，大多数被识别的模型目前不适合临床使用，主要是由于方法学上的缺陷和潜在的偏倚。 为了解决这些问题，我们提供了改进建议，以提高模型质量和研究实践，从而促进具有临床实用价值的AI产品的开发。 显示英文摘要

摘要： Artificial intelligence (AI) methodologies hold great promise for the rapid and accurate diagnosis of coronary artery disease (CAD) from intravascular optical coherent tomography (IVOCT) images. Numerous papers have been published describing AI-based models for different diagnostic tasks, yet it remains unclear which models have potential clinical utility and have been properly validated. This systematic review considered published literature between January 2015 and February 2023 describing AI-based diagnosis of CAD using IVOCT. Our search identified 5,576 studies, with 513 included after initial screening and 35 studies included in the final systematic review after quality screening. Our findings indicate that most of the identified models are not currently suitable for clinical use, primarily due to methodological flaws and underlying biases. To address these issues, we provide recommendations to improve model quality and research practices to enhance the development of clinically useful AI products.