Article

Comparison of Large Language Models’ Performance on Neurosurgical Board Examination Questions

2025-02-24

Abstract excerpt

<h4>Background</h4> Multiple-choice board examinations are a primary objective measure of competency in medicine. Large language models (LLMs) have demonstrated rapid improvements in performance on medical board examinations in the past two years. We evaluated five leading LLMs on neurosurgical board exam questions. <h4>Methods</h4> We evaluated five LLMs (OpenAI o1, OpenEvidence, Claude 3.5 Sonnet, Gemini 2.0, an...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: cb1f3341-1b4e-5246-818e-2956371c3c79
DOI: 10.1101/2025.02.20.25322623

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Comparison of Large Language Models’ Performance on Neurosurgical Board Examination QuestionsDOI 10.1101/2025.02.20.25322623Read

Performance of Advanced Large Language Models (GPT-4o, GPT-4, Gemini 1.5 Pro, Claude 3 Opus) on Japanese Medical Licensing Examination: A Comparative StudySemantic proximity Read

Comparative Evaluation the Knowledge of Large Language Models about Response Evaluation Criteria in Solid Tumors?Semantic proximity Read

Comparative Performance of General-Purpose Large Language Models and a Specialized Clinical AI Tool on OKAP-Style Ophthalmology QuestionsSemantic proximity Read

Evaluating the Performance of Large Language Models on a Neurology Board-Style ExaminationSemantic proximity Read

Board-Level Performance of Leading Open-Weight Vision-Language Models on the Japanese Diagnostic Radiology Board Examination: Reasoning, Image-Input, and Language EffectsSemantic proximity Read

Multimodal Large Language Model Passes Specialty Board Examination and Surpasses Human Test-Taker Scores: A Comparative Analysis Examining the Stepwise Impact of Model Prompting Strategies on PerformanceSemantic proximity Read

Diagnostic Performance of Large Language Models and Radiologists in Case-Based Radiology QuestionsSemantic proximity Read

Textbook-Level Medical Knowledge in Large Language Models: A Comparative Evaluation Using the Japanese National Medical ExaminationSemantic proximity Read

Benchmarking the Confidence of Large Language Models in Clinical QuestionsSemantic proximity Read

ChatGPT Goes to Operating Room: Evaluating GPT-4 Performance and Its Potential in Surgical Education and Training in the Era of Large Language ModelsSemantic proximity Read

An interdisciplinary, randomized, single-blind evaluation of state-of-the-art large language models for their implications and risks in medical diagnosis and managementSemantic proximity Read

Performance of o1 pro and GPT-4 in self-assessment questions for nephrology board renewalSemantic proximity Read