Can AI pass the written European Board Examination in Neurological Surgery? - Ethical and practical issues

Artificial intelligence (AI) based large language models (LLM) contain enormous potential in education and training. Recent publications demonstrated that they are able to outperform participants in written medical exams. We aimed to explore the accuracy of AI in the written part of the EANS board e...

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Bibliographic Details
Published in:Brain & spine 2024-01, Vol.4, p.102765-102765, Article 102765
Main Authors: Stengel, Felix C., Stienen, Martin N., Ivanov, Marcel, Gandía-González, María L., Raffa, Giovanni, Ganau, Mario, Whitfield, Peter, Motov, Stefan
Format: Article
Language:English
Subjects:
Artificial intelligence
Bard
Bing
Board-certification
Chat gpt
EANS
Neurosurgery board examination
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Summary:Artificial intelligence (AI) based large language models (LLM) contain enormous potential in education and training. Recent publications demonstrated that they are able to outperform participants in written medical exams. We aimed to explore the accuracy of AI in the written part of the EANS board exam. Eighty-six representative single best answer (SBA) questions, included at least ten times in prior EANS board exams, were selected by the current EANS board exam committee. The questions’ content was classified as 75 text-based (TB) and 11 image-based (IB) and their structure as 50 interpretation-weighted, 30 theory-based and 6 true-or-false. Questions were tested with Chat GPT 3.5, Bing and Bard. The AI and participant results were statistically analyzed through ANOVA tests with Stata SE 15 (StataCorp, College Station, TX). P-values of
ISSN:2772-5294
2772-5294
DOI:10.1016/j.bas.2024.102765