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

Çamur, Eren; Cesur, Turay; Güneş, Yasin Celal · JCO Glob Oncol · 2024

cross_sectional · Level IV

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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.

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