Izvorni znanstveni članak
https://doi.org/10.3325/cmj.2024.65.93
Exploring ChatGPT’s abilities in medical article writing and peer review
Gültekin Kadi
; Department of Emergency Medicine, Gazi University Faculty of Medicine, Ankara, Turkey
*
Mehmet Ali Aslaner
; Department of Emergency Medicine, Gazi University Faculty of Medicine, Ankara, Turkey
* Dopisni autor.
Sažetak
Aim To evaluate the quality of ChatGPT-generated case
reports and assess the ability of ChatGPT to peer review
medical articles.
Methods This study was conducted from February to April
2023. First, ChatGPT 3.0 was used to generate 15 case reports, which were then peer-reviewed by expert human
reviewers. Second, ChatGPT 4.0 was employed to peer review 15 published short articles.
Results ChatGPT was capable of generating case reports,
but these reports exhibited inaccuracies, particularly when
it came to referencing. The case reports received mixed ratings from peer reviewers, with 33.3% of professionals recommending rejection. The reports’ overall merit score was
4.9±1.8 out of 10. The review capabilities of ChatGPT were
weaker than its text generation abilities. The AI as a peer
reviewer did not recognize major inconsistencies in articles
that had undergone significant content changes.
Conclusion While ChatGPT demonstrated proficiency in
generating case reports, there were limitations in terms of
consistency and accuracy, especially in referencing.
Ključne riječi
Hrčak ID:
331940
URI
Datum izdavanja:
30.4.2024.
Posjeta: 178 *