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医生:机器学习与医学的未来。

eDoctor: machine learning and the future of medicine.

机构信息

Royal Victoria Hospital, Belfast, UK.

Interventional Radiology Service, Northern Hospital Radiology, Epping, Vic, Australia.

出版信息

J Intern Med. 2018 Dec;284(6):603-619. doi: 10.1111/joim.12822. Epub 2018 Sep 3.

Abstract

Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found within medicine and feel that ML is the future for biomedical research, personalized medicine, computer-aided diagnosis to significantly advance global health care. However, the concepts of ML are unfamiliar to many medical professionals and there is untapped potential in the use of ML as a research tool. In this article, we provide an overview of the theory behind ML, explore the common ML algorithms used in medicine including their pitfalls and discuss the potential future of ML in medicine.

摘要

机器学习(ML)是医学领域的一个新兴领域,大量资源被应用于融合计算机科学和统计学来解决医学问题。ML 的支持者称赞其处理大型、复杂和异类数据的能力,这些数据通常存在于医学领域,他们认为 ML 是生物医学研究、个性化医学、计算机辅助诊断的未来,可以显著提高全球医疗保健水平。然而,许多医学专业人员对 ML 的概念并不熟悉,因此 ML 作为研究工具的潜力尚未得到充分利用。在本文中,我们提供了 ML 背后的理论概述,探讨了医学中常用的常见 ML 算法及其缺陷,并讨论了 ML 在医学中的未来潜力。

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