Serdar Babacan

Benchmarking Large Language Models (LLMs) Against Medical Students Using Psychometrically Evaluated Authentic Clinically Oriented Anatomy Multiple-Choice Questions (MCQs) at the Apply and Analyze Levels of Bloom's Taxonomy.

Current-generation LLMs achieved uniform, ceiling-level accuracy on clinically oriented anatomy MCQs at both the Apply and Analyze cognitive levels, significantly exceeding student performance, and were unaffected by the item difficulty and discrimination properties that meaningfully differentiated student performance.