Purpose of Review

This paper investigates present uses and future potential of artificial intelligence (AI) applied to intracoronary imaging technologies.

Recent Findings

Advances in data analytics and digitized medical imaging have enabled clinical application of AI to improve patient outcomes and reduce costs through better diagnosis and enhanced workflow. Applications of AI to IVUS and IVOCT have produced improvements in image segmentation, plaque analysis, and stent evaluation. Machine learning algorithms are able to predict future coronary events through the use of imaging results, clinical evaluations, laboratory tests, and demographics.

Summary

The application of AI to intracoronary imaging holds significant promise for improved understanding and treatment of coronary heart disease. Even in these early stages, AI has demonstrated the ability to improve the prediction of cardiac events. Large curated data sets and databases are needed to speed the development of AI and enable testing and comparison among algorithms.

中文翻译：

---

冠状动脉内成像中的人工智能。

审查目的

本文研究了应用于冠状动脉内成像技术的人工智能（AI）的当前用途和未来潜力。

最近的发现

数据分析和数字化医学成像技术的进步使AI的临床应用得以改善诊断并增强了工作流程，从而改善了患者的治疗效果并降低了成本。AI在IVUS和IVOCT上的应用在图像分割，斑块分析和支架评估方面取得了进步。机器学习算法能够通过使用成像结果，临床评估，实验室测试和人口统计学来预测未来的冠状动脉事件。

概要

AI在冠状动脉内成像中的应用为改善对冠心病的了解和治疗具有重大前景。即使在这些早期阶段，AI仍显示出改善心脏事件预测的能力。需要大量精选的数据集和数据库来加速AI的开发，并实现算法之间的测试和比较。