Article

PrecLLM: A Privacy-Preserving Framework for Efficient Clinical Annotation Extraction from Unstructured EHRs using Small-Scale LLMs

2026-04-27

Abstract excerpt

<title>Abstract</title> <p>Large Language Models (LLMs) have demonstrated remarkable proficiency in automated text annotation within natural language processing. However, their deployment in clinical settings is severely constrained by strict privacy regulations and the prohibitive computational cost of processing voluminous unstructured Electronic Health Records (EHRs). Unstructured EHR typically include crucial...

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Literature Corpus work: d8cfe7cf-efe7-5ef3-8b00-35976e655e9b
DOI: 10.21203/rs.3.rs-9203956/v1

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