Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model through Prompt Tuning

arXiv:2403.13089v1 Announce Type: new
Abstract: Automatic text summarization (ATS) is an emerging technology to assist clinicians in providing continuous and coordinated care. This study presents an approach to summarize doctor-patient dialogues using generative large language models (LLMs). We developed prompt-tuning algorithms to instruct generative LLMs to summarize clinical text. We examined the prompt-tuning strategies, the size of soft prompts, and the few-short learning ability of GatorTronGPT, a generative clinical LLM developed using 277 billion clinical and general English words with …

abstract algorithms arxiv ats clinicians continuous cs.cl doctor emerging technology generative language language model language models large language large language model large language models llms patient prompt prompt tuning study summarization technology text text summarization through type