Towards Adapting Open-Source Large Language Models for Expert-Level Clinical Note Generation

arXiv:2405.00715v1 Announce Type: new
Abstract: Large Language Models (LLMs) have shown promising capabilities in handling clinical text summarization tasks. In this study, we demonstrate that a small open-source LLM can be effectively trained to generate high-quality clinical notes from outpatient patient-doctor dialogues. We achieve this through a comprehensive domain- and task-specific adaptation process for the LLaMA-2 13 billion parameter model. This process incorporates continued pre-training, supervised fine-tuning, and reinforcement learning from both AI and human feedback. We introduced an enhanced …

abstract arxiv capabilities clinical cs.ai cs.cl cs.lg doctor domain expert generate language language models large language large language models llm llms notes patient quality small study summarization tasks text text summarization through type