Mlodzinski Eric, Stone David J, Celi Leo A
Department of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA.
MIT Critical Data, Laboratory for Computational Physiology, Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Pulm Ther. 2020 Jun;6(1):67-77. doi: 10.1007/s41030-020-00110-z. Epub 2020 Feb 5.
Machine learning (ML) is a discipline of computer science in which statistical methods are applied to data in order to classify, predict, or optimize, based on previously observed data. Pulmonary and critical care medicine have seen a surge in the application of this methodology, potentially delivering improvements in our ability to diagnose, treat, and better understand a multitude of disease states. Here we review the literature and provide a detailed overview of the recent advances in ML as applied to these areas of medicine. In addition, we discuss both the significant benefits of this work as well as the challenges in the implementation and acceptance of this non-traditional methodology for clinical purposes.
机器学习（ML）是计算机科学的一个分支，其中统计方法被应用于数据，以便基于先前观察到的数据进行分类、预测或优化。肺部和重症医学领域对这种方法的应用激增，有望提高我们诊断、治疗和更好理解多种疾病状态的能力。在此，我们回顾相关文献，并详细概述机器学习在这些医学领域应用的最新进展。此外，我们还讨论了这项工作的显著益处以及将这种非传统方法用于临床目的在实施和接受方面所面临的挑战。
