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November 28, 2025BJOG An International Journal of Obstetrics & GynaecologyOpen Access

Assessing the Accuracy of Large Language Models on European Guidelines for Cervical Cancer: An In Silico Benchmarking Study

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Authors

MPMatteo PavoneCIChiara InnocenziNMNicola Macellari

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Overview

Comparative benchmarking reveals that large language models show varying accuracy in cervical cancer guidelines, indicating the need for oversight.

Key Points

  • ChatGPT 4.0 achieved the highest recorded Global Quality Score of 4.00 for cervical cancer guidelines compliance, highlighting its superior performance.
  • Cervical cancer-related questions assessed included fifty derived from the ESGO/ESTRO/ESP guidelines, conveying critical relevance to clinical practice.
  • The study utilized a benchmarking approach by assessing accuracy, consistency, and reliability of language models simultaneously across multiple trials on guideline questions.
  • Findings suggest that while all models maintained consistency, reliance on them alone is insufficient without expert review for clinical safety.

Cite This Study

Pavone et al. (2025) studied this question.

synapsesocial.com/papers/6928f126a65b730b9ea7a3dfhttps://doi.org/10.1111/1471-0528.70095
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