Artificial intelligence in Oral Medicine and Radiology: It’s Knowledge, Attitude and Perception among Dental Students - Qanita, Maryam; Safi, Sanna; Arif, Fatima (ADVANCES IN BASIC MEDICAL SCIENCES, 2026)
OBJECTIVES: To determine the knowledge, attitude, and perception of dental students towards use of AI in oral medicine and radiology. METHODOLOGY: This cross-sectional study, conducted at KMU-IDS, Kohat, included 125 dental students, using a convenience sampling technique. Data was collected using a pre-validated questionnaire. The questionnaire consisted of a series of closed-ended questions to assess KAP. About 7 questions were knowledge-related, 4 questions each, regarding attitude and perception. Categorical variables were analyzed using frequencies. Modified Likert scale was used. Mean ± SD of scores of knowledge, attitude, and perception for each qualification was calculated. Comparison of the Mean ± SD of KAP domains among qualification groups was done using the Kruskal-Wallis test. Percentile scores were checked, and categorization was done for each individual. The relationship between KAP domains was checked using Spearman's Rank Correlation Coefficient. RESULTS: Around 66.4% (n=83) of participants agreed that for the detection of oral cancer and the diagnosis of mucosal lesions, AI can be employed (p =0.005). Around 72.8% (n=91) suggested that dental practitioners must use AI in their clinical practices (p value= 0.035). About 51.2% demonstrated excellent knowledge with a percentage score exceeding 75%. All 125 participants (100%) reflected a positive attitude. About 120 participants (96%) indicated a positive perception. A weak positive correlation between attitude and perception of participants was found statistically significant (p value < 0.001). CONCLUSION: This was the first-ever study in Pakistan focusing on artificial intelligence in relation to Oral Medicine and Radiology. Most of the participants had good knowledge, attitude, and perception.