From Zero-Shot to Bedside: A Practical Playbook for Adapting Open-Source Large Language Models to Clinical Symptom Extraction.

Li-Ching Chen^1,2,3, Travis Zack^2,3,4, Divneet Mandair², Aditya Mahadevan², Arvind Suresh², Yuta Ishiyama², Yiping Li⁴, Julian C Hong^2,3, Autl J Butte²

¹UC Berkeley.

²UCSF.

³Weill Cancer Hub West.

⁴OpenEvidence.

PubMed PMC PDF

Abstract

Large language models (LLMs) are increasingly applied to clinical notes, but guidance on how to adapt open-source models to specific tasks and manage annotation quality at scale is limited. We present a playbook for fine-tuning LLMs on de-identified clinical notes from patients with pancreatic cancer, spanning both pre-diagnosis and on-treatment settings. We evaluate prompting strategies, contrast…

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