Article

Comparison of Large Language Models Versus Traditional Information Extraction Methods for Real World Evidence of Patient Symptomatology in Acute and Post-Acute Sequelae of SARS-CoV-2

2024-09-20

Abstract excerpt

Patient symptoms play a critical role in disease progression and diagnosis, yet they are most often captured in unstructured clinical notes. This study explores use of large language models (LLMs) for extracting patient symptoms from clinical notes, comparing their performance against rule-based information extraction (IE) systems, like BioMedICUS. By fine-tuning an LLM on diverse corpora from multiple healthcare...

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Literature Corpus work: 72d59fb2-f625-595a-9d1a-b3a793aa0170
DOI: 10.20944/preprints202409.1518.v1

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