Classification performance and reproducibility of GPT-4 omni for information extraction from veterinary electronic health records
Large language models (LLMs) can extract information from veterinary electronic health records (EHRs), but performance differences between models, the effect of hyperparameter settings, and the influence of text ambiguity have not been previously evaluated. This study addresses these gaps by compari...
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Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-01-01
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Series: | Frontiers in Veterinary Science |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fvets.2024.1490030/full |
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