Addressing the Challenge of Biomedical Data Inequality: An Artificial Intelligence Perspective.

ABSTRACT: Artificial intelligence (AI) and other data-driven technologies hold great promise to transform healthcare and confer the predictive power essential to precision medicine. However, the existing biomedical data, which are a vital resource and foundation for developing medical AI models, do not reflect the diversity of the human population. The low representation in biomedical data has become a significant health risk for non-European populations, and the growing application of AI opens a new pathway for this health risk to manifest and amplify. Here we review the current status of biomedical data inequality and present a conceptual framework for understanding its impacts on machine learning. We also discuss the recent advances in algorithmic interventions for mitigating health disparities a

SUBMITTER: Gao Y 

PROVIDER: S-EPMC10529864 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature