Comparison of Performance of Large Language Models on Lung-RADS Related Questions-Reference-Cited by-同舟云学术

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Comparison of Performance of Large Language Models on Lung-RADS Related Questions

Published:2024-08 Issue:10 Volume: Page:
ISSN:2687-8941
Container-title:JCO Global Oncology
language:en
Short-container-title:JCO Glob Oncol

Author:

Çamur Eren¹^ORCID,Cesur Turay¹^ORCID,Güneş Yasin Celal¹

Affiliation:

1. Eren Çamur, MD, Department of Radiology, Ministry of Health Ankara 29 Mayis State Hospital, Ankara, Turkey; Turay Cesur, MD, Department of Radiology, Ankara Mamak State Hospital, Ankara, Turkey; Yasin Celal Güneş, MD, Department of Radiology, TC Saglik Bakanligi Kirikkale Yuksek Ihtisas Hastanesi, Kırıkkale, Turkey

Abstract

This study evaluates LLM integration in interpreting Lung-RADS for lung cancer screening, highlighting their innovative role in enhancing radiological practice. Our findings reveal that Claude 3 Opus and Perplexity achieved a 96% accuracy rate, outperforming other models.

Publisher

American Society of Clinical Oncology (ASCO)

Link

https://ascopubs.org/doi/pdfdirect/10.1200/GO.24.00200

Reference5 articles.

1. Comparative Evaluation of the Accuracies of Large Language Models in Answering VI-RADS-Related Questions

2. Accuracies of large language models in answering radiation protection questions

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