ChatGPT versus the neurosurgical written boards: a comparative analysis of artificial intelligence/machine learning performance on neurosurgical board–style questions

Author:

Hopkins Benjamin S.1,Nguyen Vincent N.1,Dallas Jonathan1,Texakalidis Pavlos2,Yang Max1,Renn Alex1,Guerra Gage1,Kashif Zain1,Cheok Stephanie1,Zada Gabriel1,Mack William J.1

Affiliation:

1. Department of Neurological Surgery, University of Southern California, Los Angeles, California; and

2. Department of Neurological Surgery, Northwestern University’s Feinberg School of Medicine, Chicago, Illinois

Publisher

Journal of Neurosurgery Publishing Group (JNSPG)

Subject

Genetics,Animal Science and Zoology

Reference31 articles.

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2. A systematic review on machine learning in neurosurgery: the future of decision-making in patient care;Celtikci E,2018

3. Machine learning and artificial intelligence in neurosurgery: status, prospects, and challenges;Dagi TF,2021

4. Machine learning-based surgical planning for neurosurgery: artificial intelligent approaches to the cranium;Dundar TT,2022

5. Mass deployment of deep neural network: real-time proof of concept with screening of intracranial hemorrhage using an open data set;Hopkins BS,2022

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