1. Sternberg RJ. Intelligence. Dialogues Clin Neurosci. 2012;14(1):19-27. doi:10.31887/DCNS.2012.14.1/rsternberg
2. Pinto Dos Santos D, Giese D, Brodehl S, et al. Medical students’ attitude towards Artificial Intelligence: a multicentre survey. Eur Radiol. 2019; 29(4):1640-1646. doi:10.1007/s00330-018-5601-1
3. Karan-Romero M, Salazar-Gamarra RE, Leon-Rios XA. Evaluation of attitudes and perceptions in students about the Use of Artificial Intelligence in Dentistry. Dent J. 2023;11:5. doi:10.3390/dj11050125
4. Ayad N, Schwendicke F, Krois J, et al. Patients’ perspectives on the use of Artificial Intelligence in dentistry: a regional survey. Head Face Med. 2023;19(1):23. doi:10.1186/s13005-023-00368-z
5. Vishwanathaiah S, Fageeh HN, Khanagar SB, Maganur PC. Artificial Intelligence its uses and application in pediatric dentistry: a review. Biomedicines. 2023;11:3. doi:10.3390/biomedicines11030788
6. Pauwels R, Del Rey YC. Attitude of Brazilian dentists and dental students regarding the future role of Artificial Intelligence in oral radiology: a multicenter survey. Dentomaxillofac Radiol. 2021;50(5):20200461. doi:10.1259/dmfr.20200461
7. Shakya RR. Artificial Intelligence in pediatric dentistry. J Nepalese Assoc Pediatr Dent. 2022;3(1):47-49.
8. Ellakany P, Tauqir S, Ali S, Mikhail SS. Artificial Intelligence usage among dental students/dentists of different educational level: a multi-country survey. BMC Oral Health. 2025;26(1):81. doi:10.1186/s12903-025-07476-z
9. Sadeep H. Assessment of knowledge and awareness of Artificial Intelligence and its uses in dentistry among dental students. J Pharmaceut Negat Res. 2022;13. doi:10.47750/pnr.2022.13.S04.155
10. Lim SS, Bouffanais R. ‘Data dregs’ and its implications for AI ethics: revelations from the pandemic. AI Ethics. 2022;2(4):595-597. doi:10.1007/s43681-021-00130-8
11. Claman D, Sezgin E. Artificial Intelligence in dental education: opportunities and challenges of large language models and multimodal foundation models. JMIR Med Educ. 2024;10:e52346. doi:10.2196/52346
12. Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Intern Med. 2018;178(11):1544-1547. doi:10.1001/jamainternmed.2018.3763
13. Dashti M, Londono J, Ghasemi S, et al. Attitudes, knowledge, and perceptions of dentists and dental students toward Artificial Intelligence: a systematic review. J Taibah Univ Med Sci. 2024;19(2):327-337. doi:10.1016/j.jtumed.2023.12.010
14. Mörch CM, Atsu S, Cai W, et al. Artificial Intelligence and ethics in dentistry: a scoping review. J Dent Res. 2021;100(13):1452-1460. doi:10. 1177/00220345211013808
15. Yüzbaşıoğlu E. Attitudes and perceptions of dental students towards Artificial Intelligence. J Dent Educ. 2021;85(1):60-68. doi:10.1002/jdd. 12385
16. Thurzo A, Strunga M, Urban R, Surovková J, Afrashtehfar KI. Impact of Artificial Intelligence on dental education: a review and guide for curriculum update. Educat Sci. 2023;13(2):150. doi:10.3390/educsci 13020150
17. Islam NM, Laughter L, Sadid-Zadeh R, et al. Adopting Artificial Intelligence in dental education: a model for academic leadership and innovation. J Dent Educ. 2022;86(11):1545-1551. doi:10.1002/jdd.13010
18. Keser G, Pekiner FMN. Attitudes, perceptions and knowledge regarding the future of Artificial Intelligence in oral radiology among a group of dental students in Turkiye: a survey. Clin Experiment Health Sci. 2021;11(4):637-641. doi:10.33808/clinexphealthsci.928246
19. Elchaghaby M, Wahby R. Knowledge, attitudes, and perceptions of a group of Egyptian dental students toward Artificial Intelligence: a cross-sectional study. BMC Oral Health. 2025;25(1):11. doi:10.1186/s12903-024-05282-7
20. Oh S, Kim JH, Choi SW, Lee HJ, Hong J, Kwon SH. Physician confidence in Artificial Intelligence: an online mobile survey. J Med Internet Res. 2019;21(3):e12422. doi:10.2196/12422
21. Sur J, Bose S, Khan F, Dewangan D, Sawriya E, Roul A. Knowledge, attitudes, and perceptions regarding the future of Artificial Intelligence in oral radiology in India: a survey. Imaging Sci Dent. 2020;50(3):193-198. doi:10.5624/isd.2020.50.3.193
22. Roganovic J, Radenkovic M, Milicic B. Responsible use of Artificial Intelligence in dentistry: survey on dentists’ and final-year undergraduates’ perspectives. Healthcare. 2023;11:10. doi:10.3390/healthcare11101480
23. Seram T, Batra M, Gijwani D, Chauhan K, Jaggi M, Kumari N. Attitude and perception of dental students towards Artificial Intelligence. Univ J Dent Sci. 2021;7:3. doi:10.21276/ujds.2021.7.3.13
24. Bisdas S, Topriceanu CC, Zakrzewska Z, et al. Artificial Intelligence in medicine: a multinational multi-center survey on the medical and dental students’ perception. Front Public Health. 2021;9:795284. doi:10. 3389/fpubh.2021.795284
25. Hegde S, Nanayakkara S, Jordan A, et al. Attitudes and perceptions of Australian dentists and dental students towards applications of Artificial Intelligence in dentistry: a survey. Eur J Dent Educ. 2025;29(1):9-18. doi:10.1111/eje.13042
26. Kosan E, Krois J, Wingenfeld K, Deuter CE, Gaudin R, Schwendicke F. Patients’ perspectives on Artificial Intelligence in dentistry: a controlled study. J Clin Med. 2022;11:8. doi:10.3390/jcm11082143
27. Khanagar S, Alkathiri M, Alhamlan R, Alyami K, Alhejazi M, Alghamdi A. Knowledge, attitudes, and perceptions of dental students towards Artificial Intelligence in Riyadh, Saudi Arabia. Med Sci. 2021;25(114): 1857-1867.
28. Jeong H, Han SS, Jung HI, Lee W, Jeon KJ. Perceptions and attitudes of dental students and dentists in South Korea toward Artificial Intelligence: a subgroup analysis based on professional seniority. BMC Med Educ. 2024;24(1):430. doi:10.1186/s12909-024-05441-y
29. Sahin E. Gender equity in education. Open J Soc Sci. 2013;2(1):59-63. doi:10.4236/jss.2014.21007
30. Kahveci FS, Özel İ, Gümüştaş B. Assessing student attitudes and perceptions toward the use of Artificial Intelligence in dentistry. Essent Dent. 2024;3(2):51-55. doi:10.5152/EssentDent.2024.23028
31. Yılmaz C, Erdem RZ, Uygun LA. Artificial Intelligence knowledge, attitudes and application perspectives of undergraduate and specialty students of faculty of dentistry in Turkiye: an online survey research. BMC Med Educ. 2024;24(1):1149. doi:10.1186/s12909-024-06106-6
32. Bonny T, Al Nassan W, Obaideen K, Al Mallahi MN, Mohammad Y, El-Damanhoury HM. Contemporary role and applications of Artificial Intelligence in dentistry. F1000Res. 2023;12:1179. doi:10.12688/f1000 research.140204.1
33. Vodanovic M, Subašic M, Miloševic D, Savic Pavicin I. Artificial Intelligence in medicine and dentistry. Acta Stomatol Croat. 2023;57(1): 70-84. doi:10.15644/asc57/1/8
34. Tartuk BK. The role of Artificial Intelligence in prosthetic dentistry. Dent Med J Rev. 2025;7(2):71-87.
35. Amiri H, Peiravi S, Rezazadeh Shojaee SS, et al. Medical, dental, and nursing students’ attitudes and knowledge towards Artificial Intelligence: a systematic review and meta-analysis. BMC Med Educ. 2024;24(1):412. doi:10.1186/s12909-024-05406-1
36. Charow R, Jeyakumar T, Younus S, et al. Artificial Intelligence education programs for health care professionals: scoping review. JMIR Med Educ. 2021;7(4):e31043. doi:10.2196/31043
37. Keshavarz P, Mohammadigoldar Z, Bedayat A, Raman SS, Tai R. Artificial Intelligence education in radiology training: a systematic review of effectiveness, barriers, and future directions. Acad Radiol. 2026;33(3):695-706. doi:10.1016/j.acra.2025.10.049
38. Rokhshad R, Ducret M, Chaurasia A, et al. Ethical considerations on Artificial Intelligence in dentistry: a framework and checklist. J Dent. 2023;135:104593. doi:10.1016/j.jdent.2023.104593
39. Pethani F. Promises and perils of Artificial Intelligence in dentistry. Aust Dent J. 2021;66(2):124-135. doi:10.1111/adj.12812
40. Chau MT, Spuur KM, White S, Pyper A, Crossman M. Malpractice in the machine age: legal and ethical responses to machine learning in medical imaging. Radiography. 2026;32(3):103339. doi:10.1016/j.radi. 2026.103339
41. Tandon D, Rajawat J. Present and future of Artificial Intelligence in dentistry. J Oral Biol Craniofac Res. 2020;10(4):391-396. doi:10.1016/j.jobcr.2020.07.015