Towards Fairer Health Recommendations: Finding Informative Unbiased Samples via Word Sense Disambiguation

    September 2024 in “ arXiv (Cornell University) ”
    Gavin Butts, Pegah Emdad, jeong-in Lee, Shannon Song, Chiman Salavati, Willmar Sosa Diaz, Shiri Dori-Hacohen, Fabrício Murai
    Image

    Preprint — not peer reviewed.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 evaluated various NLP models for detecting bias in medical curricula, finding that fine-tuned BERT models perform well, whereas LLMs, despite being state-of-the-art in many tasks, are unsuitable for this application.
    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
    Discuss this study in the Community →