Closing the AI Generalization Gap by Adjusting for Dermatology Condition Distribution Differences Across Clinical Settings

    February 2024 in “ arXiv (Cornell University) ”
    Rajeev Rikhye, Aaron Loh, Grace Hong … Steven Lin

    Preprint — not peer reviewed. This was posted to a preprint server or data repository. It has not been through a journal's review process, and its findings may change or not hold up.

    Studysummary In this study, researchers found that differences in skin condition distribution are the main source of errors when AI algorithms classify dermatological conditions from new, previously unseen sources, and proposed steps to improve their generalizability based on available information.
    Automatically generated from the study's abstract, not written by a person, and not a review of the full paper. Not medical advice or a treatment recommendation. Read the original study, and consult a qualified healthcare professional before changing treatment. Full disclaimer
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