Department of Internal Medicine/Cardiology, Heart Center Leipzig at University of Leipzig, Struempellstr. 39, 04289, Leipzig, Germany.
Leipzig Heart Institute, Leipzig Heart Science at Heart Center Leipzig, Leipzig, Germany.
Basic Res Cardiol. 2023 Mar 20;118(1):10. doi: 10.1007/s00395-023-00982-7.
A modern-day physician is faced with a vast abundance of clinical and scientific data, by far surpassing the capabilities of the human mind. Until the last decade, advances in data availability have not been accompanied by analytical approaches. The advent of machine learning (ML) algorithms might improve the interpretation of complex data and should help to translate the near endless amount of data into clinical decision-making. ML has become part of our everyday practice and might even further change modern-day medicine. It is important to acknowledge the role of ML in prognosis prediction of cardiovascular disease. The present review aims on preparing the modern physician and researcher for the challenges that ML might bring, explaining basic concepts but also caveats that might arise when using these methods. Further, a brief overview of current established classical and emerging concepts of ML disease prediction in the fields of omics, imaging and basic science is presented.
现代医生面临着大量的临床和科学数据，这些数据远远超出了人类大脑的能力。直到过去十年，数据可用性的进步并没有伴随着分析方法的进步。机器学习 (ML) 算法的出现可能会改善对复杂数据的解释，并有助于将近乎无限量的数据转化为临床决策。ML 已经成为我们日常实践的一部分，甚至可能进一步改变现代医学。承认 ML 在心血管疾病预后预测中的作用非常重要。本综述旨在为现代医生和研究人员准备好迎接 ML 可能带来的挑战，解释基本概念，但也说明在使用这些方法时可能出现的警告。此外，还简要概述了当前在组学、成像和基础科学领域中建立的经典和新兴的 ML 疾病预测概念。
