Lammers Daniel T, Eckert Carly M, Ahmad Muhammad A, Bingham Jason R, Eckert Matthew J
From the Department of Surgery, Madigan Army Medical Center, Tacoma, WA.
Department of Epidemiology, University of Washington, Seattle, WA.
Ann Surg Open. 2021 Sep 7;2(3):e091. doi: 10.1097/AS9.0000000000000091. eCollection 2021 Sep.
Machine learning (ML) represents a collection of advanced data modeling techniques beyond the traditional statistical models and tests with which most clinicians are familiar. While a subset of artificial intelligence, ML is far from the science fiction impression frequently associated with AI. At its most basic, ML is about pattern finding, sometimes with complex algorithms. The advanced mathematical modeling of ML is seeing expanding use throughout healthcare and increasingly in the day-to-day practice of surgeons. As with any new technique or technology, a basic understanding of principles, applications, and limitations are essential for appropriate implementation. This primer is intended to provide the surgical reader an accelerated introduction to applied ML and considerations in potential research applications or the review of publications, including ML techniques.
机器学习（ML）代表了一系列先进的数据建模技术，超越了大多数临床医生所熟悉的传统统计模型和测试方法。作为人工智能的一个子集，ML与通常与人工智能相关联的科幻印象相去甚远。最基本地说，ML就是关于模式发现，有时会使用复杂的算法。ML的先进数学建模在整个医疗保健领域的应用越来越广泛，在外科医生的日常实践中也越来越常见。与任何新技术或技术一样，对其原理、应用和局限性有基本的了解对于正确实施至关重要。本入门指南旨在为外科领域的读者提供对应用ML的快速介绍，以及在潜在研究应用或出版物综述（包括ML技术）中的注意事项。
