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Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students

Year 2026, Volume: 18 Issue: 1 , 1 - 13 , 30.04.2026
https://doi.org/10.56484/iamr.1902406
https://izlik.org/JA64HE27TE

Abstract

Objective: The aim of this study was to multidimensionally evaluate clinical-period dental students' awareness, knowledge levels, attitudes, expectations, and potential concerns regarding AI applications.
Methods: The study population consisted of fourth and fifth-year students in the clinical training period at the Dicle University Faculty of Dentistry. Data were collected using a structured questionnaire developed by the researchers. Items related to attitudes and opinions were evaluated using a 5-point Likert scale. Categorical variables were compared between groups using Pearson's Chi-square and Fisher's exact tests. The SPSS (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.) program was used for statistical analyses, and a significance level of p<0.05 was accepted.
Results: Of the 200 students who participated in the study, 43.5% reported positive awareness of AI. The highest positive views were observed for radiographic caries assessment (82.5%) and implant planning (81.5%). A significant difference was found between classes in terms of the necessity of informed consent (p=0.035).
Conclusion: Clinical-period dental students generally have a positive attitude toward AI and believe it will make significant contributions, particularly in education and clinical applications. The findings highlight the need to integrate structured AI content into dental education programs.

References

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  • Fernandes S, Bafna Y. Knowledge, attitude and practice of dental students towards artificial intelligence: a questionnaire-based survey. J Xidian Univ. 2022;16(8):284-291. doi:10.37896/jxu16.8/029.
  • Shrateh ON, Al-Batat S, Al-Qudimat AR, Ghannam LI, Abuhanoud LJ. Attitudes and perceptions of dental students towards artificial intelligence. BMC Med Educ. 2025;25(1):1386.
  • Yuzbasioglu E. Attitudes and perceptions of dental students towards artificial intelligence. J Dent Educ. 2021;85(1):60-68.
  • Bisdas S, Topriceanu CC, Zakrzewska Z, et al. Artificial intelligence in medicine: a multinational multi-center survey on medical and dental students’ perception. Front Public Health. 2021;9:795284. doi:10.3389/fpubh.2021.795284.
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  • Pinto Dos Santos D, Giese D, Brodehl S, et al. Medical students’ attitude towards artificial intelligence: a multicenter survey. Eur Radiol. 2019;29(4):1640-1646.
  • Gallix B, Chong J. Artificial intelligence in radiology: who’s afraid of the big bad wolf? Eur Radiol. 2019;29:1637-1639.
  • Lee JH, Kim DH, Jeong SN, Choi SH. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. J Dent. 2018;77:106-111.
  • Vishwanathaiah S, Fageeh HN, Khanagar SB, Maganur PC. Artificial intelligence: its uses and application in pediatric dentistry: a review. Biomedicines. 2023;11:788.
  • Khanagar SB, Alfouzan K, Awawdeh M, et al. Application and performance of artificial intelligence technology in detection, diagnosis and prediction of dental caries: a systematic review. Diagnostics (Basel). 2022;12:1083.
  • Abouzeid HL, Chaturvedi S, Abdelaziz KM, et al. Role of robotics and artificial intelligence in oral health and preventive dentistry: knowledge, perception and attitude of dentists. Oral Health Prev Dent. 2021;19:353-363.
  • Smith A, Anderson M. Automation in Everyday Life. Washington (DC): Pew Research Center; 2017.
  • Demetriou C, Ozer BU, Essau CA. Self-report questionnaires. In: Cautin RL, Lilienfeld SO, editors. The Encyclopedia of Clinical Psychology. Hoboken (NJ): John Wiley & Sons; 2015. p.1-6.
  • Alzahrani AAH. Perceptions and attitudes of dental practitioners toward robotic dentistry and artificial intelligence in Saudi Arabia. AIP Adv. 2024;14(4).

Year 2026, Volume: 18 Issue: 1 , 1 - 13 , 30.04.2026
https://doi.org/10.56484/iamr.1902406
https://izlik.org/JA64HE27TE

Abstract

References

  • Eroglu Cakmakoglu E, Gunay A. Dental students’ opinions on use of artificial intelligence: a survey study. Med Sci Monit. 2025;31:3674-3678.
  • Ahmed N, Abbas MS, Zuber F, et al. Artificial intelligence techniques: analysis, application, and outcome in dentistry: a systematic review. Biomed Res Int. 2021;2021:9751564. doi:10.1155/2021/9751564.
  • Wang W, Siau K. Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity. J Database Manag. 2019;30(1):61-79. doi:10.4018/JDM.2019010104.
  • Bickman L. Improving mental health services: a 50-year journey from randomized experiments to artificial intelligence and precision mental health. Adm Policy Ment Health. 2020;47(5):795-843. doi:10.1007/s10488-020-01065-8.
  • LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436-444. doi:10.1038/nature14539.
  • Gulshan V, Peng L, Coram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA. 2016;316(22):2402-2410.
  • Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115-118.
  • Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018;2(10):719-731.
  • Reddy S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare delivery. J R Soc Med. 2019;112(1):22-28.
  • Cakmakoglu EE. The place of ChatGPT in the future of dental education. J Clin Trials Exp Investig. 2023;2(3):121-129.
  • Agrawal P, Nikhade P. Artificial intelligence in dentistry: past, present, and future. Cureus. 2022;14(7):e27405. doi:10.7759/cureus.27405.
  • Fatani B. ChatGPT for future medical and dental research. Cureus. 2023;15(4):e37285. doi:10.7759/cureus.37285.
  • Alhaidry HM, Fatani B, Alrayes JO, Almana AM, Alfhaed NK. ChatGPT in dentistry: a comprehensive review. Cureus. 2023;15(4):e38317. doi:10.7759/cureus.38317.
  • Liu L, Watanabe M, Ichikawa T. Robotics in dentistry: a narrative review. Dent J (Basel). 2023;11:62.
  • Wood EA, Ange BL, Miller DD. Are we ready to integrate artificial intelligence literacy into medical school curriculum? Students and faculty survey. J Med Educ Curric Dev. 2021;8:23821205211024078.
  • Maliha G, Gerke S, Cohen IG, Parikh RB. Artificial intelligence and liability in medicine: balancing safety and innovation. Milbank Q. 2021;99:629-647.
  • Verghese A, Shah NH, Harrington RA. What this computer needs is a physician: humanism and artificial intelligence. JAMA. 2018;319(1):19-20.
  • Yousef M, Deeb S, Alhashlamon K. AI usage among medical students in Palestine: a cross-sectional study and demonstration of AI-assisted research workflows. BMC Med Educ. 2025. doi:10.1186/s12909-025-07272-x.
  • Sur J, Bose S, Khan F, et al. 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.
  • Fernandes S, Bafna Y. Knowledge, attitude and practice of dental students towards artificial intelligence: a questionnaire-based survey. J Xidian Univ. 2022;16(8):284-291. doi:10.37896/jxu16.8/029.
  • Shrateh ON, Al-Batat S, Al-Qudimat AR, Ghannam LI, Abuhanoud LJ. Attitudes and perceptions of dental students towards artificial intelligence. BMC Med Educ. 2025;25(1):1386.
  • Yuzbasioglu E. Attitudes and perceptions of dental students towards artificial intelligence. J Dent Educ. 2021;85(1):60-68.
  • Bisdas S, Topriceanu CC, Zakrzewska Z, et al. Artificial intelligence in medicine: a multinational multi-center survey on medical and dental students’ perception. Front Public Health. 2021;9:795284. doi:10.3389/fpubh.2021.795284.
  • Ozel S, Buyukcavus MH. Examining dental students' thoughts on artificial intelligence applications in dentistry. 7tepe Clin J. 2022;18(2):55-60.
  • Pinto Dos Santos D, Giese D, Brodehl S, et al. Medical students’ attitude towards artificial intelligence: a multicenter survey. Eur Radiol. 2019;29(4):1640-1646.
  • Gallix B, Chong J. Artificial intelligence in radiology: who’s afraid of the big bad wolf? Eur Radiol. 2019;29:1637-1639.
  • Lee JH, Kim DH, Jeong SN, Choi SH. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. J Dent. 2018;77:106-111.
  • Vishwanathaiah S, Fageeh HN, Khanagar SB, Maganur PC. Artificial intelligence: its uses and application in pediatric dentistry: a review. Biomedicines. 2023;11:788.
  • Khanagar SB, Alfouzan K, Awawdeh M, et al. Application and performance of artificial intelligence technology in detection, diagnosis and prediction of dental caries: a systematic review. Diagnostics (Basel). 2022;12:1083.
  • Abouzeid HL, Chaturvedi S, Abdelaziz KM, et al. Role of robotics and artificial intelligence in oral health and preventive dentistry: knowledge, perception and attitude of dentists. Oral Health Prev Dent. 2021;19:353-363.
  • Smith A, Anderson M. Automation in Everyday Life. Washington (DC): Pew Research Center; 2017.
  • Demetriou C, Ozer BU, Essau CA. Self-report questionnaires. In: Cautin RL, Lilienfeld SO, editors. The Encyclopedia of Clinical Psychology. Hoboken (NJ): John Wiley & Sons; 2015. p.1-6.
  • Alzahrani AAH. Perceptions and attitudes of dental practitioners toward robotic dentistry and artificial intelligence in Saudi Arabia. AIP Adv. 2024;14(4).
There are 33 citations in total.

Details

Primary Language English
Subjects Dentistry (Other)
Journal Section Research Article
Authors

Suzan Cangül 0000-0002-1546-7688

Özkan Adıgüzel 0000-0001-6089-3013

Makbule Taşyürek 0009-0008-5183-4474

Tuba Tunç 0000-0003-2513-9386

Hatice Ortaç 0000-0002-1199-1706

Submission Date March 4, 2026
Acceptance Date April 15, 2026
Publication Date April 30, 2026
DOI https://doi.org/10.56484/iamr.1902406
IZ https://izlik.org/JA64HE27TE
Published in Issue Year 2026 Volume: 18 Issue: 1

Cite

APA Cangül, S., Adıgüzel, Ö., Taşyürek, M., Tunç, T., & Ortaç, H. (2026). Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students. International Archives of Medical Research, 18(1), 1-13. https://doi.org/10.56484/iamr.1902406
AMA 1.Cangül S, Adıgüzel Ö, Taşyürek M, Tunç T, Ortaç H. Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students. IAMR. 2026;18(1):1-13. doi:10.56484/iamr.1902406
Chicago Cangül, Suzan, Özkan Adıgüzel, Makbule Taşyürek, Tuba Tunç, and Hatice Ortaç. 2026. “Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students”. International Archives of Medical Research 18 (1): 1-13. https://doi.org/10.56484/iamr.1902406.
EndNote Cangül S, Adıgüzel Ö, Taşyürek M, Tunç T, Ortaç H (April 1, 2026) Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students. International Archives of Medical Research 18 1 1–13.
IEEE [1]S. Cangül, Ö. Adıgüzel, M. Taşyürek, T. Tunç, and H. Ortaç, “Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students”, IAMR, vol. 18, no. 1, pp. 1–13, Apr. 2026, doi: 10.56484/iamr.1902406.
ISNAD Cangül, Suzan - Adıgüzel, Özkan - Taşyürek, Makbule - Tunç, Tuba - Ortaç, Hatice. “Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students”. International Archives of Medical Research 18/1 (April 1, 2026): 1-13. https://doi.org/10.56484/iamr.1902406.
JAMA 1.Cangül S, Adıgüzel Ö, Taşyürek M, Tunç T, Ortaç H. Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students. IAMR. 2026;18:1–13.
MLA Cangül, Suzan, et al. “Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students”. International Archives of Medical Research, vol. 18, no. 1, Apr. 2026, pp. 1-13, doi:10.56484/iamr.1902406.
Vancouver 1.Suzan Cangül, Özkan Adıgüzel, Makbule Taşyürek, Tuba Tunç, Hatice Ortaç. Are Dental Students Ready For Artificial Intelligence? Evaluation Of Knowledge, Attitudes, And Perceived Concerns Among Clinical-Year Students. IAMR. 2026 Apr. 1;18(1):1-13. doi:10.56484/iamr.1902406

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