Excited to share that our work on interpretable risk prediction will be at the #NAACL2024 main conference!

Our work on reducing diagnostic errors with interpretable risk prediction is now on arXiv! We retrieve evidence from a patient’s record, visualize how it informs a prediction, and test it in a realistic setting. 👇 (1/6) arxiv.org/abs/2402.10109 w/ @byron.bsky.social and @jwvdm.bsky.social

Very excited our “CHiLL” paper was accepted to #EMNLP2023 Findings! Can we craft arbitrary high-level features without training?👇(1/6) We ask a doctor to ask questions to an LLM and train an interpretable model on the answers. arxiv.org/abs/2302.12343 w/ @jwvdm.bsky.social and @byron.bsky.social