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Faster, better?: Testing artificial intelligence accuracy for neurosurgical literature analysis
Serkan Civlan1, Berk Burak Berker2, Defne Şahinoğlu Berker2
1Department of Neurosurgery, Pamukkale University, School of Medicine, Denizli, Türkiye.
Medicine
|December 16, 2025
Summary
ChatPDF demonstrates 89% accuracy in interpreting neurosurgery research articles, showing potential as an AI tool for academic tasks. However, manual verification is crucial due to inconsistent source reliability.
Area of Science:
- Neurosurgery
- Artificial Intelligence
- Medical Informatics
Background:
- Artificial intelligence (AI) tools like ChatPDF offer potential for neurosurgery academic tasks.
- Critical assessment of AI tool accuracy and relevance in specialized fields is necessary.
Purpose of the Study:
- To evaluate the accuracy and reliability of ChatPDF in interpreting neurosurgical research articles.
- To identify the strengths and limitations of ChatPDF for neurosurgical literature review.
Main Methods:
- Selected original research articles from top 10 neurosurgery journals (2023 volume).
- Generated 10 researcher-posed questions per article.
- Uploaded articles to ChatPDF for question generation and response provision.
- Assessed response accuracy (completely correct, partially correct, incorrect) and source reliability.
Main Results:
- ChatPDF achieved an overall accuracy rate of 89% across 100 questions.
- 89% of responses were completely correct, 5% partially correct, and 6% incorrect.
- Average source reliability was 83%, with noted variability across journals.
Conclusions:
- ChatPDF shows substantial accuracy and potential as a supplementary tool for neurosurgical literature review.
- Limitations include inconsistent source reliability and inability to analyze visual content.
- Manual verification remains essential for comprehensive and accurate interpretation of neurosurgical research.
