Artificial intelligence (AI) has emerged as a promising tool for enhancing diagnostic accuracy. This study investigated AI-assisted detection of periapical lesions on digital periapical radiographs. A dataset of 500 radiographs was analyzed by a convolutional neural network (CNN) model. The model achieved a sensitivity of 92% and specificity of 89%, outperforming conventional radiographic interpretation by general dentists. Integration of AI into routine dental radiology workflows could enable earlier lesion detection and improved patient outcomes.

Keywords:
Artificial Intelligence, Periapical Lesions, Digital Radiography, CNN, Diagnostic Accuracy