Feb. 20, 2024, 5:43 a.m. | Salman Rahman, Lavender Yao Jiang, Saadia Gabriel, Yindalon Aphinyanaphongs, Eric Karl Oermann, Rumi Chunara

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.10965v1 Announce Type: cross
Abstract: Advances in large language models (LLMs) provide new opportunities in healthcare for improved patient care, clinical decision-making, and enhancement of physician and administrator workflows. However, the potential of these models importantly depends on their ability to generalize effectively across clinical environments and populations, a challenge often underestimated in early development. To better understand reasons for these challenges and inform mitigation approaches, we evaluated ClinicLLM, an LLM trained on [HOSPITAL]'s clinical notes, analyzing its performance on …

abstract advances arxiv clinical cs.cl cs.cy cs.lg decision environments evaluation healthcare healthcare ai language language model language models large language large language model large language models llms making opportunities patient patient care type workflows

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