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Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare
April 26, 2024, 4:41 a.m. | Emre Can Acikgoz, Osman Batur \.Ince, Rayene Bench, Arda An{\i}l Boz, \.Ilker Kesen, Aykut Erdem, Erkut Erdem
cs.LG updates on arXiv.org arxiv.org
Abstract: The integration of Large Language Models (LLMs) into healthcare promises to transform medical diagnostics, research, and patient care. Yet, the progression of medical LLMs faces obstacles such as complex training requirements, rigorous evaluation demands, and the dominance of proprietary models that restrict academic exploration. Transparent, comprehensive access to LLM resources is essential for advancing the field, fostering reproducibility, and encouraging innovation in healthcare AI. We present Hippocrates, an open-source LLM framework specifically developed for the …
abstract academic arxiv cs.ai cs.cl cs.lg diagnostics evaluation exploration framework healthcare integration language language models large language large language models llms medical obstacles patient patient care proprietary proprietary models requirements research training type
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