Attitude and perception of dental students towards artificial intelligence

  • Tampha Seram Dept of public health dentistry,Surendera dental college and research institute
  • Manu Batra
  • Deeksha Gijwani
  • Krishna Chauhan
  • Manya Jaggi
  • Neelam Kumari
Keywords: Artificial intelligence, knowledge, dental students


Introduction-Artificial intelligence has been advancing in fields including anesthesiology,radiologist, dentist. The study is conducted to test out knowledge,attitude and future among undergraduate and postgraduatedental students of Sri Ganganagar, Rajasthan.

Material and Methods-This is a cross sectional questionnaire-based study, conducted among undergraduate students and postgraduate students in dental institute of Sri Ganganagar, Rajasthan.Pre-tested and validated questionnaire was sent to students through Google form. Descriptive statistics surveyed the frequency distribution and Chi-square test assessed the difference in perception among the study population.

Results-More than 226 (81%) were undergraduate dental students and around 53 (19 %) were postgraduate students. About 55.8 % undergraduate students and 77.4% post graduatestudents had mentioned that they are familiar with the uses and knowledge of AI. For idea of how AI can be incorporated in dental practice, around 36.7% undergraduate students and 20.8% post graduate students responded positively. It showed undergraduate students had higher knowledge idea about how AI can be incorporated in dental practice, this difference in opinion was found to be statistically significant (p = 0.001).

Conclusion-AI will be useful in planning diagnosis and treatment planned in future by seeing respond from respondents. The lectures and seminars could be organized to make that dental students gain a better understanding of AI and ultimately helped them play a fully conscious and active role in the development, implementation and use of AI tools in dentistry.



1. SchwendickleSamek F,Krois J. Artificial Intelligence in Dentistry: Chances and Challenges. J Dent Res 2020; 99(7):769–774.
2. Hashimoto DA, Witkowski E, Gao L, MeirelesO,Rosman G. Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.2020;132(2) 379-394.
3. Balyen L, Peto T. Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology. Asia pac J Ophthalmol (Phila) 2019;,8(3): 264-272.
4. Hwang JJ, Jung YH, Cho BH, Heo MS. An overview of deep learning in the field of dentistry. Imaging Sci Dent 2019; 49: 1-7.
5. 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.
6. Pakdemirli E. Artificial intelligence in radiology: friend or foe? Where are we now and where are we heading? Acta Ra diol Open 2019; 8: 205.
7. Inkster B, Sarda S, Subramanian V. An empathy-driven, conversational artificial intelligence agent (Wysa) for digital mental well-being: real-world data evaluation mixed-methods study. JMIR MhealthUhealth. 2018;6(11):12106.
8. Krittanawong C. The rise of artificial intelligence and the uncertain future for physicians. Eur J Intern Med. 2018;48:13- 14.
How to Cite
Seram, T., Batra, M., Gijwani, D., Chauhan, K., Jaggi, M., & Kumari, N. (2021). Attitude and perception of dental students towards artificial intelligence. UNIVERSITY JOURNAL OF DENTAL SCIENCES, 7(3).

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