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Large Language Models Are Poor Medical Coders — Benchmarking of Medical Code Querying
110
Zitationen
8
Autoren
2024
Jahr
Abstract
BACKGROUND Large language models (LLMs) have attracted significant interest for automated clinical coding. However, early data show that LLMs are highly error-prone when mapping medical codes. We sought to quantify and benchmark LLM medical code querying errors across several available LLMs.
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