AI models for tasks such as pathology and dermatology struggle to generalize to new patient groups or hospitals that they were not trained on; learning more robust features from unlabeled data could prevent overfitting to the training distribution and thereby increase fairness.
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Movva, R., Koh, P.W. & Pierson, E. Using unlabeled data to enhance fairness of medical AI. Nat Med 30, 944–945 (2024). https://doi.org/10.1038/s41591-024-02892-0
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DOI: https://doi.org/10.1038/s41591-024-02892-0
