Bias recognition and mitigation strategies in artificial intelligence healthcare applications.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 40069303.
- Also identified by DOI 10.1038/s41746-025-01503-7 and PMC identifier 11897215.
- Licence recorded as CC BY-NC-ND.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Artificial intelligence (AI) is delivering value across all aspects of clinical practice. However, bias may exacerbate healthcare disparities. This review examines the origins of bias in healthcare AI, strategies for mitigation, and responsibilities of relevant stakeholders towards achieving fair and equitable use. We highlight the importance of systematically identifying bias and engaging relevant mitigation activities throughout the AI model lifecycle, from model conception through to deployment and longitudinal surveillance.