Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data

JAMA Network August 20, 2018
Milena A. Gianfrancesco, PhD, MPH; Suzanne Tamang, PhD, MS; Jinoos Yazdany, MD, MPH; Gabriela Schmajuk, MD, MS

A promise of machine learning in health care is the avoidance of biases in diagnosis and treatment; a computer algorithm could objectively synthesize and interpret the data in the medical record. Integration of machine learning with clinical decision support tools, such as computerized alerts or diagnostic support, may offer physicians and others who provide health care targeted and timely information that can improve clinical decisions. Machine learning algorithms, however, may also be subject to biases. The biases include those related to missing data and patients not identified by algorithms, sample size and...

Today's Sponsors

Today's Sponsor