Deep Learning and Artificial Intelligence in Health Care

After years of development, machine learning methods have matured enough to be used in clinical medicine. In 2018 the FDA approved software to screen patients for diabetic retinopathy, and the methods are rapidly making their way into other applications for image analysis, natural language processing, EHR data mining, drug discovery, and more. JAMA is proud to be a primary forum for the work of interdisciplinary groups demonstrating the use of machine learning methods for clinical medicine and health care.

Review

Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data

Milena A. Gianfrancesco and Coauthors

JAMA Internal Medicine | Special Communication, November 2018

On Deep Learning for Medical Image Analysis

Lawrence Carin and Michael J. Pencina

JAMA | JAMA Guide to Statistics and Methods, September 18, 2018

Not Just Digital Pathology, Intelligent Digital Pathology

Balazs Acs and David L. Rimm

JAMA Oncology | From The JAMA Network, March 2018

Opinion

Questions for Artificial Intelligence in Health Care

Thomas M. Maddox and Coauthors

JAMA | Viewpoint, December 10, 2018

Humanizing Artificial Intelligence

Sonoo Thadaney Israni and Abraham Verghese

JAMA | Viewpoint, December 10, 2018

Clinical Decision Support in the Era of Artificial Intelligence

Edward H. Shortliffe and Martin J. Sepúlveda

JAMA | Viewpoint, November 5, 2018

On the Prospects for a (Deep) Learning Health Care System

C. David Naylor

JAMA | Viewpoint, September 18, 2018

On Deep Learning for Medical Image Analysis

Lawrence Carin and Michael J. Pencina

JAMA | JAMA Guide to Statistics and Methods, September 18, 2018

Deep Learning—A Technology With the Potential to Transform Health Care

Geoffrey Hinton

JAMA | Viewpoint, September 18, 2018

Big Data and Predictive Analytics: Recalibrating Expectations

Nilay D. Shah and Coauthors

JAMA | Viewpoint, July 3, 2018

Big Data and Machine Learning in Health Care

Andrew L. Beam and Isaac S. Kohane

JAMA | Viewpoint, April 3, 2018

What This Computer Needs Is a Physician: Humanism and Artificial Intelligence

Abraham Verghese and Coauthors

JAMA | Viewpoint, January 2, 2018

Unintended Consequences of Machine Learning in Medicine

Federico Cabitza and Coauthors

JAMA | Viewpoint, August 8, 2017

Artificial Intelligence With Deep Learning Technology Looks Into Diabetic Retinopathy Screening

Tien Yin Wong and Neil M. Bressler

JAMA | Editorial, December 13, 2016

Adapting to Artificial Intelligence: Radiologists and Pathologists as Information Specialists

Saurabh Jha and Eric J. Topol

JAMA | Viewpoint, December 13, 2016

Translating Artificial Intelligence Into Clinical Care

Andrew L. Beam and Isaac S. Kohane

JAMA | Editorial, December 13, 2016

Machine Learning and the Profession of Medicine

Alison M. Darcy and Coauthors

JAMA | Viewpoint, February 9, 2016

Related Multimedia

Understanding How Machine Learning Works

Interview with Sonoo Thadaney-Israni, MBA, and Abraham Verghese, MD, MACP, authors of Humanizing Artificial Intelligence

More Machine Learning From JAMA Network

Estimating Retinal Sensitivity Using Optical Coherence Tomography With Deep-Learning Algorithms in Macular Telangiectasia Type 2

Yuka Kihara and Coauthors

JAMA Network Open | Original Investigation, February 8, 2019

Machine Learning–Based Prediction of Clinical Outcomes for Children During Emergency Department Triage

Tadahiro Goto and Coauthors

JAMA Network Open | Original Investigation, January 11, 2019

Machine Learning in Clinical Medicine Still Finding Its Way

Dickson S. Cheung and Joseph A. Grubenhoff

JAMA Network Open | Invited Commentary, January 11, 2019

Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration

Philippe M. Burlina and Coauthors

JAMA Ophthalmology | Original Investigation, January 10, 2019

Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks

Philipp Tschandl and Coauthors

JAMA Dermatology | Original Investigation, January 2019

Validation of Prediction Models for Critical Care Outcomes Using Natural Language Processing of Electronic Health Record Data

Ben J. Marafino and Coauthors

JAMA Network Open | Original Investigation, December 21, 2018

Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma

Stuart Keel and Coauthors

JAMA Ophthalmology | Brief Report, December 20, 2018

Deep Learning in Medicine—Promise, Progress, and Challenges

Fei Wang and Coauthors

JAMA Internal Medicine | Viewpoint, December 17, 2018

Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks

Philipp Tschandl and Cliff Rosendahl

JAMA Dermatology | Original Investigation, November 28, 2018

Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients

Maxwell Taggart and Coauthors

JAMA Network Open | Original Investigation, October 12, 2018

Evaluation of Artificial Intelligence–Based Grading of Diabetic Retinopathy in Primary Care

Yogesan Kanagasingam and Coauthors

JAMA Network Open | Original Investigation, September 28, 2018

Evaluating Artificial Intelligence Applications in Clinical Settings

Elaine O. Nsoesie

JAMA Network Open | Invited Commentary, September 28, 2018

Use of Deep Learning to Examine the Association of the Built Environment With Prevalence of Neighborhood Adult Obesity

Adyasha Maharana and Elaine Okanyene Nsoesie

JAMA Network Open | Original Investigation, August 31, 2018

Machine Learning for Prediction in Electronic Health Data

Sherri Rose

JAMA Network Open | Invited Commentary, August 3, 2018

Machine Learning and Health Care Disparities in Dermatology

Adewole S. Adamson and Avery Smith

JAMA Dermatology | Viewpoint, August 1, 2018

A Machine Learning Approach for Automated Facial Measurements in Facial Palsy

Diego L. Guarin and Coauthors

JAMA Facial Plastic Surgery | Observation, Jul/Aug 2018

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

James M. Brown and Coauthors

JAMA Ophthalmology | Original Investigation, July 2018

Machine Learning and the Prediction of Hydrocephalus: Can Quantitative Image Analysis Assist the Clinician?

Peter A. Chiarelli and Coauthors

JAMA Pediatrics | Editorial, February 2018

Machine Learning Models for Prediction of Reinjury After Penetrating Trauma

Joshua Parreco and Rishi Rattan

JAMA Surgery | Research Letter, February 2018

Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks

Philippe M. Burlina and Coauthors

JAMA Ophthalmology | Original Investigation, November 2017

Will Machine Learning Tip the Balance in Breast Cancer Screening?

Andrew D. Trister and Coauthors

JAMA Oncology | Viewpoint, November 2017

The Potential of Radiomic-Based Phenotyping in Precision Medicine: A Review

Hugo J. W. L. Aerts

JAMA Oncology | Review, December 2016

Determining Electroconvulsive Therapy Response With Machine Learning

Christopher C. Abbott and Coauthors

JAMA Psychiatry | Editorial, June 2016

Clinical Vestibular Testing Assessed With Machine-Learning Algorithms

Adrian J. Priesol and Coauthors

JAMA Otolaryngology | Original Investigation, April 2015