Bias Mitigation in Primary Health Care Artificial Intelligence Models: Scoping Review.

ABSTRACT:

Background

Artificial intelligence (AI) predictive models in primary health care have the potential to enhance population health by rapidly and accurately identifying individuals who should receive care and health services. However, these models also carry the risk of perpetuating or amplifying existing biases toward diverse groups. We identified a gap in the current understanding of strategies used to assess and mitigate bias in primary health care algorithms related to individuals' personal or protected attributes.

Objective

This study aimed to describe the attempts, strategies, and methods used to mitigate bias in AI models within primary health care, to identify the diverse groups or protected attributes considered, and to evaluate the results of these approaches on both

SUBMITTER: Sasseville M 

PROVIDER: S-EPMC11751650 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature