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

共 50 条

[1] Deep Learning for Epidemiologists: An Introduction to Neural Networks
Serghiou, Stylianos
Rough, Kathryn
[J]. AMERICAN JOURNAL OF EPIDEMIOLOGY, 2023, 192 (11) : 1904 - 1916
[2] Neural networks and deep learning: a brief introduction
Georgevici, Adrian Iustin
Terblanche, Marius
[J]. INTENSIVE CARE MEDICINE, 2019, 45 (05) : 712 - 714
[3] Neural networks and deep learning: a brief introduction
Adrian Iustin Georgevici
Marius Terblanche
[J]. Intensive Care Medicine, 2019, 45 : 712 - 714
[4] Advances in Machine Learning and Deep Neural Networks
Chellappa, Rama
Theodoridis, Sergios
van Schaik, Andre
[J]. PROCEEDINGS OF THE IEEE, 2021, 109 (05) : 607 - 611
[5] Deep Neural Networks and Explainable Machine Learning
Maratea, Antonio
Ferone, Alessio
[J]. FUZZY LOGIC AND APPLICATIONS, WILF 2018, 2019, 11291 : 253 - 256
[6] Machine learning with neural networks: an introduction for scientists and engineers
Probert, Matt
[J]. CONTEMPORARY PHYSICS, 2021, 62 (04) : 236 - 237
[7] Machine learning and deep learning: Introduction and applications
Nakashima T.
[J]. Nakashima, Tomoharu, 1600, Society of Materials Science Japan (69): : 633 - 639
[8] Machine Learning and Deep Neural Networks in Thoracic and Cardiovascular Imaging
Retson, Tara A.
Besser, Alexandra H.
Sall, Sean
Golden, Daniel
Hsiao, Albert
[J]. JOURNAL OF THORACIC IMAGING, 2019, 34 (03) : 192 - 201
[9] Machine Learning in Neural Networks
Lin, Eugene
Tsai, Shih-Jen
[J]. FRONTIERS IN PSYCHIATRY: ARTIFCIAL INTELLIGENCE, PRECISION MEDICINE, AND OTHER PARADIGM SHIFTS, 2019, 1192 : 127 - 137
[10] Online Deep Learning: Learning Deep Neural Networks on the Fly
Sahoo, Doyen
Pham, Quang
Lu, Jing
Hoi, Steven C. H.
[J]. PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 2660 - 2666

← 1 2 3 4 5 →