Bias Assessment and Data Drift Detection in Medical Image Analysis: A Survey

    September 2024 in “ arXiv (Cornell University) ”
    Andrea Prenner, Bernhard Kainz, Kainz, Bernhard

    Preprint — not peer reviewed.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 This study reviews methods to ensure the reliability of machine learning models in medical imaging, focusing on bias detection, data drift assessment, and accuracy estimation without ground truth labels to enhance integration into clinical settings.
    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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