Detecting Caries Using AI A group of researchers led by Dr. Mohammad Moharrami, a PhD student and dental public health resident at the University of Toronto, published a systemic review to evaluate the performance of artificial intelligence (AI) models in detecting dental caries from intraoral photographs.1 The review found that AI may assist with oral health screening, clinical decision-making and facilitate communication between patients and clinicians, as well as teledentistry. In terms of clinical decision-making, the review suggests that AI models might perform better at detecting primary caries compared to secondary caries, likely due to the variability in the clinical presentation of secondary caries and the smaller number of labeled secondary caries in the data sets. Furthermore, studies that used AI that included professional and intraoral camera images as the source of data collection performed better than those that used smartphone images. However, further research is needed in this area, with a focus on implementing more robust study designs, employing standardized metrics, larger datasets and addressing the severity of caries lesions. CDA brought together some of the researchers—Drs. Michael Glogauer, Sonica Singhal and Mohammad Moharrami—to discuss the study as well as the larger implications of the potential use of AI in dentistry. The conversation has been edited for length and clarity. 20 | 2025 | Issue 1
RkJQdWJsaXNoZXIy OTE5MTI=