Department of Surgery, Division of Vascular Surgery (A.M.F., F.D., N.J.L., E.G.R.), Stanford University School of Medicine, CA.
Department of Medicine, Division of Cardiovascular Medicine (N.J.L.), Stanford University School of Medicine, CA.
Circ Res. 2021 Jun 11;128(12):1833-1850. doi: 10.1161/CIRCRESAHA.121.318224. Epub 2021 Jun 10.
Peripheral artery disease is an atherosclerotic disorder which, when present, portends poor patient outcomes. Low diagnosis rates perpetuate poor management, leading to limb loss and excess rates of cardiovascular morbidity and death. Machine learning algorithms and artificially intelligent systems have shown great promise in application to many areas in health care, such as accurately detecting disease, predicting patient outcomes, and automating image interpretation. Although the application of these technologies to peripheral artery disease are in their infancy, their promises are tremendous. In this review, we provide an introduction to important concepts in the fields of machine learning and artificial intelligence, detail the current state of how these technologies have been applied to peripheral artery disease, and discuss potential areas for future care enhancement with advanced analytics.
外周动脉疾病是一种动脉粥样硬化性疾病，存在时预示着患者预后不良。低诊断率导致管理不善，导致肢体丧失和心血管发病率和死亡率过高。机器学习算法和人工智能系统在外科领域的许多应用中显示出巨大的应用前景，例如准确检测疾病、预测患者预后和自动图像解释。尽管这些技术在外周动脉疾病中的应用还处于起步阶段，但它们的前景非常广阔。在这篇综述中，我们介绍了机器学习和人工智能领域的一些重要概念，详细介绍了这些技术在外周动脉疾病中的应用现状，并讨论了利用高级分析技术增强未来护理的潜在领域。
