A. Butte

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

A playbook for fine-tuning LLMs on de-identified clinical notes from patients with pancreatic cancer, spanning both pre-diagnosis and on-treatment settings is presented, and the use of machine-generated annotations to augment limited expert labels is examined, showing that balanced mixtures of synthetic and human data can enhance fine-tuned models.