Performance of Large Language Models in Answering Critical Care Medicine Questions

Large Language Models have been tested on medical student-level questions, but their performance in specialized fields like Critical Care Medicine (CCM) is less explored. This study evaluated Meta-Llama 3.1 models (8B and 70B parameters) on 871 CCM questions. Llama3.1:70B outperformed 8B by 30%, with 60% average accuracy. Performance varied across domains, highest in Research (68.4%) and lowest in Renal (47.9%), highlighting the need for broader future work to improve models across various subspecialty domains.

Publication Details

Journal
ArXiv.org
Published
2025-09-16
Primary Topic
Historical and Cultural Archaeology Studies
Type
article
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article

Performance of Large Language Models in Answering Critical Care Medicine Questions

ArXiv.org
Historical and Cultural Archaeology Studies
article

Performance of Large Language Models in Answering Critical Care Medicine Questions

article en

Abstract

Large Language Models have been tested on medical student-level questions, but their performance in specialized fields like Critical Care Medicine (CCM) is less explored. This study evaluated Meta-Llama 3.1 models (8B and 70B parameters) on 871 CCM questions. Llama3.1:70B outperformed 8B by 30%, with 60% average accuracy. Performance varied across domains, highest in Research (68.4%) and lowest in Renal (47.9%), highlighting the need for broader future work to improve models across various subspecialty domains.

ArXiv.org
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Openalex Percentile: Top 38%
Historical and Cultural Archaeology Studies
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