Domain‐Specific Customization for Language Models in Otolaryngology: The ENT GPT Assistant

Domain‐Specific Customization for Language Models in Otolaryngology: The ENT GPT Assistant

Abstract Objective To develop and evaluate the effectiveness of domain‐specific customization in large language models (LLMs) by assessing the performance of the ENT GPT Assistant (E‐GPT‐A), a model specifically tailored for otolaryngology. Study Design Comparative analysis using multiple‐choice que...

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Bibliographic Details
Main Authors: Brenton T. Bicknell, Nicholas J. Rivers, Adam Skelton, Delaney Sheehan, Charis Hodges, Stevan C. Fairburn, Benjamin J. Greene, Bharat Panuganti
Format: Article
Language:English
Published: Wiley 2025-04-01
Series:OTO Open
Subjects:
artificial intelligence
comprehensive otolaryngology
machine learning
natural language processing
Online Access:https://doi.org/10.1002/oto2.70125
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https://doi.org/10.1002/oto2.70125

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