Publication Date
4-1-2023
Journal
The Journal of Ambulatory Care Management
DOI
10.1097/JAC.0000000000000453
PMID
36649491
PMCID
PMC9974552
PubMedCentral® Posted Date
1-18-2024
PubMedCentral® Full Text Version
Author MSS
Published Open-Access
yes
Keywords
Humans, Artificial Intelligence, Machine Learning, Algorithms, Delivery of Health Care
Abstract
We discuss the potential for machine learning (ML) and artificial intelligence (AI) to improve health care, while detailing caveats and important considerations to ensure unbiased and equitable implementation. If disparities exist in the data used to train ML algorithms, they must be recognized and accounted for, so they do not bias performance accuracy or are not interpreted by the algorithm as simply a lack of need. We pay particular attention to an area in which bias in data composition is particularly striking, that is in large-scale genetics databases, as people of European descent are vastly overrepresented in the existing resources.
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Biological Phenomena, Cell Phenomena, and Immunity Commons, Biomedical Informatics Commons, Genetics and Genomics Commons, Medical Genetics Commons, Medical Molecular Biology Commons, Medical Specialties Commons