Large Language Model Symptom Identification from Clinical Text: A Multi-Center Study
Journal:
medRxiv
Published Date:
Jan 1, 2024
Abstract
Recognition of patient symptoms is core to medicine, research, and public health. We tested four large language models (LLMs) identifying 11 symptoms of infectious respiratory diseases from emergency department notes (N=204). Each LLM outperformed ICD-10-based identification. GPT-4 had highest tested accuracy, F1 score 91.4% vs. 45.1% for ICD-10. GPT-4 performance in an independent validation cohort (N=308) was even higher with an F1 score of 94.0%.
