April 8, 2024, 4:42 a.m. | Amin Dada, Marie Bauer, Amanda Butler Contreras, Osman Alperen Kora\c{s}, Constantin Marc Seibold, Kaleb E Smith, Jens Kleesiek

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.04067v1 Announce Type: cross
Abstract: Large Language Models (LLMs) have shown the potential to significantly contribute to patient care, diagnostics, and administrative processes. Emerging biomedical LLMs address healthcare-specific challenges, including privacy demands and computational constraints. However, evaluation of these models has primarily been limited to non-clinical tasks, which do not reflect the complexity of practical clinical applications. Additionally, there has been no thorough comparison between biomedical and general-domain LLMs for clinical tasks. To fill this gap, we present the Clinical …

arxiv clinical cs.ai cs.cl cs.lg evaluation language language understanding llms type understanding

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