Prevalence of Artificial Intelligence-Generated Text in Neurosurgical Publications: Implications for Academic Integrity and Ethical Authorship
Our findings highlight both the increasing integration of AI in manuscript preparation and a critical challenge in academic publishing as AI language models become increasingly sophisticated and traditional detection methods become less reliable. This suggests the need to shift focus from detection to transparency, emphasizing the development of clear disclosure policies and ethical guidelines for AI use in academic writing.
Authors
- Harshal Shah (ORCID: https://orcid.org/0000-0003-0047-4890)
- Jacob Gluski (ORCID: https://orcid.org/0000-0002-7024-3273)
- Max Ward (ORCID: https://orcid.org/0000-0001-9114-7339)
- Sheng-Fu Larry Lo (ORCID: https://orcid.org/0000-0001-7262-2544)
- Daniel M. Sciubba (ORCID: https://orcid.org/0000-0001-7604-434X)
- Ethan Brown (ORCID: https://orcid.org/0009-0003-6933-0745)
- Daniel Schneider (ORCID: https://orcid.org/0000-0003-3465-9738)
- Akash Mishra (ORCID: https://orcid.org/0000-0003-2023-3269)
Institutions
- Donald & Barbara Zucker School of Medicine at Hofstra/Northwell (US)
Publication Details
- Journal
- Cureus
- Published
- 2025-02-16
- DOI
- https://doi.org/10.7759/cureus.79086
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96