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Comparison of Performance of Large Language Models on Lung-RADS Related Questions
Eren Çamur1, Turay Cesur1, Yasin Celal Güneş1
1Eren 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.

