A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study.

ABSTRACT:

Background

Racial disparities in health care are well documented in the United States. As machine learning methods become more common in health care settings, it is important to ensure that these methods do not contribute to racial disparities through biased predictions or differential accuracy across racial groups.

Objective

The goal of the research was to assess a machine learning algorithm intentionally developed to minimize bias in in-hospital mortality predictions between white and nonwhite patient groups.

Methods

Bias was minimized through preprocessing of algorithm training data. We performed a retrospective analysis of electronic health record data from patients admitted to the intensive care unit (ICU) at a large academic health center between 2001 and 2012,

SUBMITTER: Allen A 

PROVIDER: S-EPMC7644374 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature