Introduction to Machine Learning, Neural Networks, and Deep Learning

被引：450

作者：

Choi, Rene Y. ^{[1
]}

Coyner, Aaron S. ^{[2
]}

Kalpathy-Cramer, Jayashree ^{[3
]}

Chiang, Michael F. ^{[1
,2
]}

Campbell, J. Peter ^{[1
]}

机构：

[1] Oregon Hlth & Sci Univ, Casey Eye Inst, Dept Ophthalmol, Portland, OR 97239 USA

[2] Oregon Hlth & Sci Univ, Dept Med Informat & Clin Epidemiol, Portland, OR 97239 USA

[3] Massachusetts Gen Hosp, Dept Radiol, Athinoula A Martinos Ctr Biomed Imaging, Charlestown, MA USA

来源：

TRANSLATIONAL VISION SCIENCE & TECHNOLOGY | 2020年 / 9卷 / 02期

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

deep learning; machine learning; artificial intelligence; ARTIFICIAL-INTELLIGENCE; PREDICTION; MODEL;

D O I：

10.1167/tvst.9.2.14

中图分类号：

R77 [眼科学];

学科分类号：

100212 ;

摘要：

Purpose: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. Methods: A systematic literature search in PubMed was performed for articles pertinent to the topic of artificial intelligence methods used in medicine with an emphasis on ophthalmology. Results: A review of machine learning and deep learning methodology for the audience without an extensive technical computer programming background. Conclusions: Artificial intelligence has a promising future in medicine; however, many challenges remain. Translational Relevance: The aim of this review article is to provide the nontechnical readers a layman's explanation of the machine learning methods being used in medicine today. The goal is to provide the reader a better understanding of the potential and challenges of artificial intelligence within the field of medicine.

引用

页数：12

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