EVALUATING LARGE LANGUAGE MODELS FOR MEDICAL INFORMATION EXTRACTION: A COMPARATIVE STUDY OF ZERO-SHOT AND SCHEMA-BASED METHODS

EVALUATING LARGE LANGUAGE MODELS FOR MEDICAL INFORMATION EXTRACTION: A COMPARATIVE STUDY OF ZERO-SHOT AND SCHEMA-BASED METHODS

This study investigates the application of large language models, particularly ChatGPT, in the extraction and structuring of medical information from free-text patient reports. The authors explore two distinct methods: a zero-shot extraction approach and a schema-based extraction approach. The datas...

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Bibliographic Details
Main Authors: Zakaria KADDARI, Ikram El HACHMI, Jamal BERRICH, Rim AMRANI, Toumi BOUCHENTOUF
Format: Article
Language:English
Published: Polish Association for Knowledge Promotion 2024-12-01
Series:Applied Computer Science
Subjects:
Medical Information Extraction
Large Language Models
ChatGPT
schema-based extraction
Online Access:https://ph.pollub.pl/index.php/acs/article/view/6532
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