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MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data

MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data

来源:Arxiv_logoArxiv
英文摘要

As large language models (LLMs) like OpenAI's GPT series continue to make strides, we witness the emergence of artificial intelligence applications in an ever-expanding range of fields. In medicine, these LLMs hold considerable promise for improving medical workflows, diagnostics, patient care, and education. Yet, there is an urgent need for open-source models that can be deployed on-premises to safeguard patient privacy. In our work, we present an innovative dataset consisting of over 160,000 entries, specifically crafted to fine-tune LLMs for effective medical applications. We investigate the impact of fine-tuning these datasets on publicly accessible pre-trained LLMs, and subsequently, we juxtapose the performance of pre-trained-only models against the fine-tuned models concerning the examinations that future medical doctors must pass to achieve certification.

Jens-Michalis Papaioannou、Tom Oberhauser、Daniel Truhn、Paul Grundmann、Alexander L?ser、Tianyu Han、Keno K. Bressem、Alexei Figueroa、Lisa C. Adams

医学现状、医学发展医学研究方法

Jens-Michalis Papaioannou,Tom Oberhauser,Daniel Truhn,Paul Grundmann,Alexander L?ser,Tianyu Han,Keno K. Bressem,Alexei Figueroa,Lisa C. Adams.MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data[EB/OL].(2023-04-14)[2025-05-14].https://arxiv.org/abs/2304.08247.点此复制

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