Meyfroidt Geert, Güiza Fabian, Ramon Jan, Bruynooghe Maurice
Department of Intensive Care Medicine, UZ Leuven--Campus Gasthuisberg, Catholic University of Leuven, Herestraat 49, 3000 Leuven, Belgium.
Best Pract Res Clin Anaesthesiol. 2009 Mar;23(1):127-43. doi: 10.1016/j.bpa.2008.09.003.
Computerization in healthcare in general, and in the operating room (OR) and intensive care unit (ICU) in particular, is on the rise. This leads to large patient databases, with specific properties. Machine learning techniques are able to examine and to extract knowledge from large databases in an automatic way. Although the number of potential applications for these techniques in medicine is large, few medical doctors are familiar with their methodology, advantages and pitfalls. A general overview of machine learning techniques, with a more detailed discussion of some of these algorithms, is presented in this review.
总体而言,医疗保健领域的计算机化程度正在上升,尤其是在手术室(OR)和重症监护病房(ICU)。这导致了具有特定属性的大型患者数据库。机器学习技术能够自动检查并从大型数据库中提取知识。尽管这些技术在医学中的潜在应用数量众多,但很少有医生熟悉其方法、优势和陷阱。本综述对机器学习技术进行了概述,并对其中一些算法进行了更详细的讨论。