1. Rashid A, Kausik MAK. AI revolutionizing industries worldwide: a comprehensive overview of its diverse applications. Hybrid Adv. 2024; 7:100277.
2. Hoffmann T, Teichgräber U, Lassen-Schmidt B, Renz D, Brüheim LB, Krämer M, et al. Artificial intelligence-based quantification of pulmonary HRCT (AIqpHRCT) for the evaluation of interstitial lung disease in patients with inflammatory rheumatic diseases. Rheumatol Int. 2024; 44(11):2483–2496. PMID:
39249141.
3. Labinsky H, Nagler LK, Krusche M, Griewing S, Aries P, Kroiß A, et al. Vignette-based comparative analysis of ChatGPT and specialist treatment decisions for rheumatic patients: results of the Rheum2Guide study. Rheumatol Int. 2024; 44(10):2043–2053. PMID:
39126460.
4. Zhao J, Long Y, Li S, Li X, Zhang Y, Hu J, et al. Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features. Rheumatol Int. 2024; 44(10):2027–2041. PMID:
39207588.
5. Carobene A, Padoan A, Cabitza F, Banfi G, Plebani M. Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process. Clin Chem Lab Med. 2024; 62(5):835–843. PMID:
38019961.
6. Khalifa M, Albadawy M. Using artificial intelligence in academic writing and research: an essential productivity tool. Comput Methods Programs Biomed Update. 2024; 5:100145.
7. Chen P, Wu L, Wang L. AI fairness in data management and analytics: a review on challenges, methodologies, and applications. Appl Sci. 2023; 13(18):10258.
8. Doskaliuk B, Zimba O. Beyond the keyboard: academic writing in the era of ChatGPT. J Korean Med Sci. 2023; 38(26):e207. PMID:
37401498.
9. Zhai C, Wibowo S, Li LD. The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learn Environ. 2024; 11(1):28.
11. Cong-Lem N, Soyoof A, Tsering D. A systematic review of the limitations and associated opportunities of ChatGPT. Int J Hum Comput Interact. 2024; 1–16.
12. Ferrara E. Fairness and bias in artificial intelligence: a brief survey of sources, impacts, and mitigation strategies. Sci. 2024; 6(1):3.
13. Farber S. Enhancing peer review efficiency: a mixed-methods analysis of artificial intelligence-assisted reviewer selection across academic disciplines. Learn Publ. 2024; 37(4):e1638.
14. Hosseini M, Horbach SPJM. Fighting reviewer fatigue or amplifying bias? Considerations and recommendations for use of ChatGPT and other large language models in scholarly peer review. Res Integr Peer Rev. 2023; 8:4. PMID:
37198671.
15. Kocak Z. Publication ethics in the era of artificial intelligence. J Korean Med Sci. 2024; 39(33):e249. PMID:
39189714.
16. Wu X, Duan R, Ni J. Unveiling security, privacy, and ethical concerns of ChatGPT. J Inf Intell. 2024; 2(2):102–115.
17. Park CW, Seo SW, Kang N, Ko B, Choi BW, Park CM, et al. Artificial intelligence in health care: current applications and issues. J Korean Med Sci. 2020; 35(42):e379. PMID:
33140591.
18. Giglio AD, Costa MUPD. The use of artificial intelligence to improve the scientific writing of non-native English speakers. Rev Assoc Med Bras. 2023; 69(9):e20230560. PMID:
37729376.
19. Hadan H, Wang DM, Mogavi RH, Tu J, Zhang-Kennedy L, Nacke LE. The great AI witch hunt: reviewers’ perception and (mis)conception of generative AI in research writing. Comput Hum Behav Artif Hum. 2024; 2(2):100095.
20. Stahl BC, Eke D. The ethics of ChatGPT – exploring the ethical issues of an emerging technology. Int J Inf Manage. 2024; 74:102700.
21. de la Torre-López J, Ramírez A, Romero JR. Artificial intelligence to automate the systematic review of scientific literature. Computing. 2023; 105(10):2171–2194.
22. Biswas SS. AI-assisted academia: navigating the nuances of peer review with ChatGPT 4. J Pediatr Pharmacol Ther. 2024; 29(4):441–445. PMID:
39144391.
23. Zimba O, Gasparyan AY. Peer review guidance: a primer for researchers. Reumatologia. 2021; 59(1):3–8. PMID:
33707789.
24. Lim WM, Bowman C. Giving and responding to feedback: guidelines for authors and reviewers. Act Adapt Aging. 2024; 48(1):1–20.
25. Lund BD, Wang T. Chatting about ChatGPT: how may AI and GPT impact academia and libraries? Libr Hi Tech News. 2023; 40(3):26–29.
26. Zhaksylyk A, Zimba O, Yessirkepov M, Kocyigit BF. Research integrity: where we are and where we are heading. J Korean Med Sci. 2023; 38(47):e405. PMID:
38050915.
27. Dwivedi YK, Kshetri N, Hughes L, Slade EL, Jeyaraj A, Kar AK, et al. Opinion paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. Int J Inf Manage. 2023; 71:102642.
28. Gasparyan AY, Yessirkepov M, Voronov AA, Koroleva AM, Kitas GD. Updated editorial guidance for quality and reliability of research output. J Korean Med Sci. 2018; 33(35):e247. PMID:
30140192.
29. Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, et al. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ. 2023; 23(1):689. PMID:
37740191.
30. Leung TI, de Azevedo Cardoso T, Mavragani A, Eysenbach G. Best practices for using AI tools as an author, peer reviewer, or editor. J Med Internet Res. 2023; 25:e51584. PMID:
37651164.
31. Flanagin A, Kendall-Taylor J, Bibbins-Domingo K. Guidance for authors, peer reviewers, and editors on use of AI, language models, and chatbots. JAMA. 2023; 330(8):702–703. PMID:
37498593.
33. Cotton DRE, Cotton PA, Shipway JR. Chatting and cheating: ensuring academic integrity in the era of ChatGPT. Innov Educ Teach Int. 2023; 61(2):228–239.
34. Kendall G. When using artificial intelligence tools in scientific publications authors should include the prompts and the generated text as part of the submission. J Acad Ethics. 2024; Forthcoming. DOI:
10.1007/s10805-024-09581-0.
35. Kocyigit BF, Zhaksylyk A. Advantages and drawbacks of ChatGPT in the context of drafting scholarly articles. Cent Asian J Med Hypotheses Ethics. 2023; 4(3):163–167.