Knowledge and awareness of dental residents regarding the applications of artificial intelligence for diagnosis and treatment planning- a cross-sectional survey

Background: With the high pace of development in technology worldwide, Artificial intelligence (AI) has given a new horizon to the world of medicine and dentistry. Numerous research studies have been carried out over the past decade that have assessed the role of Machine learning (ML) and artificial intelligence in dentistry. This study aims to evaluate dental residents’ knowledge and perception regarding AI’s application in dentistry. Methods: A validated and reliable questionnaire was circulated online among 32 dental residents. The small sample size reflects the total number of dental residents available at the study site during the data-collection period. The questionnaire consisted of 20 components, which assessed knowledge and awareness of participants regarding artificial intelligence (AI) and its uses in dentistry. The Shapiro-Wilk test was applied to assess the normality of the data. For each categorical variable, frequencies and percentages were computed. For quantitative variables such as age, the arithmetic mean and standard deviation were computed. Results: Out of the 32 participants, 26 were female residents, and the remaining six were male residents. The majority of participants had no prior experience working on AI-related projects, and 97% had never received any training on AI applications. About 31% claimed to have a basic understanding of AI’s working principles. Regarding the perceived diagnostic abilities of AI compared to humans, 15% believed AI was superior, while 65% were unsure. A significant 71% believed AI could assist in identifying minute details on radiographs often overlooked by human practitioners. Moreover, 72% expressed the possibility of using AI for diagnosis in the future, and 31% viewed AI as most helpful in making a diagnosis. Conclusions: The majority of clinicians are aware of artificial intelligence and its significance. Clinicians harbor doubt regarding the diagnostic abilities of artificial intelligence and, hence, prefer their judgment. Despite the lack of confidence, the majority believes in AI´s ability to pinpoint minor details which helps in the accurate diagnosis of dental pathologies. Basic AI skills would help clinicians learn and utilize technology to their advantage.