Perception of Artificial Intelligence in Dentistry Students
DOI:
https://doi.org/10.20453/spirat.v3iNE1.5611Keywords:
University students, artificial intelligence, Dentistry, perceptionAbstract
The incorporation of new and innovative technologies in the field of dentistry has generated significant advances and optimization of operating times in practice. This study had a quantitative approach and descriptive design, a questionnaire was applied to 220 students to evaluate the perception of Artificial Intelligence in dentistry students from a university in southern Perú. 45.9 % of those surveyed stated that they had a perception of agreement with AI in the field of dentistry, followed by 43.2 % who declared that they had no knowledge about AI; a statistically significant difference was found when measuring the association of per-ception about AI with sex (X2(gl:2; p = 0.009)), age (X2(gl:2; p = 0.015)) and academic cycle (X2(gl:2; p = 0.016)). The majority of students had a perception in agreement with AI; this perception was associated with male students, students over 21 years of age, and students in clinical academic cycles.
Downloads
References
Acharya, S., Godhi, B. S., Saxena, V., Assiry, A. A., Alessa, N. A., Dawasaz, A. A., Alqarni, A., & Karobari, M. I. (2024). Role of artificial intelligence in behavior management of pediatric dental patients—a mini review. Journal of Clinical Pediatric Dentistry, 48(3), 24. https://doi.org/10.22514/jocpd.2024.055
Amiri, H., Peiravi, S., Rezazadeh Shojaee, S. Sara, Rouhparvarzamin, M., Nateghi, M. N., Etemadi, M. H., ShojaeiBaghini, M., Musaie, F., Anvari, M. H., & Asadi Anar, M. (2024). Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis. BMC Medical Education, 24(1). https://doi.org/10.1186/S12909-024-05406-1
Ghaffari, M., Zhu, Y., & Shrestha, A. (2024). A review of advancements of artificial intelligence in dentistry. Dentistry Review, 4(2), 100081. https://doi.org/10.1016/J.DENTRE.2024.100081
Jeong, H., Han, S. S., Jung, H. I., Lee, W., & Jeon, K. J. (2024). Perceptions and atti-tudes of dental students and dentists in South Korea toward artificial intelligence: a subgroup analysis based on professional seniority. BMC Medical Education, 24(1). https://doi.org/10.1186/S12909-024-05441-Y
Karan-Romero, M., Salazar-Gamarra, R. E., & Leon-Rios, X. A. (2023). Evaluation of Attitudes and Perceptions in Students about the Use of Artificial Intelligence in Dentistry. Dentistry Journal, 11(5), 125. https://doi.org/10.3390/dj11050125
Ossowska, A., Kusiak, A., & Świetlik, D. (2022). Artificial Intelligence in Dentistry—Narrative Review. International Journal of Environmental Research and Public Health, 19(6). https://doi.org/10.3390/IJERPH19063449
Vashisht, R., Sharma, A., Kiran, T., Jolly, S. S., Brar, P. K., & Puri, J. V. (2024). Artificial intelligence in dentistry — A scoping review. Journal of Oral and Maxillofacial Surgery, Medicine, and Pathology, 36(4), 579–592. https://doi.org/10.1016/J.AJOMS.2024.04.009
Xie, B., Xu, D., Zou, X. Q., Lu, M. J., Peng, X. L., & Wen, X. J. (2024). Artificial intelligence in dentistry: A bibliometric analysis from 2000 to 2023. Journal of Dental Sciences, 19(3), 1722–1733. https://doi.org/10.1016/J.JDS.2023.10.025
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Lisette Shaily Quispe Flores, Vilma Mamani Cori, Betsy Quispe Quispe, Naysha Sharon Villanueva Alvaro

This work is licensed under a Creative Commons Attribution 4.0 International License.





1.png)







