Use of Artificial Intelligence for Caries Detection on Dental Radiographs

AbstractBackground:Dental caries, being among the most frequent oral issues, calls for careful attention. Early checks help. Without them, things can slowly get worse, sometimes before anyone even notices. Standard ways of evaluating these cases still depend heavily on clinical skill, which isn’t always consistent. Mistakes in reading the signs aren’t rare. Now, with advancements in Artificial Intelligence, the field is shifting. It’s not just about detection anymore. AI enters the scene with promise bringing shifts in how diagnosis happens, care is planned, andcases are followed. Even the utilization of thetime gets changed inclinics.Aim: To spot interproximal caries in periapical x-rays using artificial intelligence (AI). Also, to compare the efficacy of AI findings against the readings done by radiologists.Materials and Methods: A dataset of 400 periapical images was selected, representing 900 posterior teeth with suspected interproximal caries. A convolutional neural network (CNN) was trained using labelled periapical images for caries detection.