Application of Artificial Intelligence for Detection of Dental Carious Lesions in Digital Dental Radiographs: An In Vitro Study

Radiographic SampleIntraoral periapical dental radiographic images were redeemed among the image database of the Postgraduate Institute of Dental Sciences, Rohtak.Manual search of the images was done and the following exclusion criteria were applied: IntroductIonDental caries is a dynamic disease with a complex etiology.The detection of interproximal, occlusal, and other surface carious lesions is conventionally done by visual tactile examination and dental radiography.Machine learning (ML) includes a group of procedures inspired by neuronal networks and the mode of functioning of the brain, and is able to communicate and think.and operate independently.However, the application of artificial intelligence (AI) in dental radiology is poorly explored.The current study was designed with the main purpose of developing an AI model that can automatically recognize and classify attributes in digital intraoral periapical (IOPA) dental radiographic images and aid in the identification of carious lesions in an efficient manner.The primary objective of the study was to evaluate the sensitivity and specificity of the AI system in detecting dental caries on digital IOPA radiographs and to compare its diagnostic performance with that of trained human evaluator(s).The secondary objective was to use the AI system to categorize dental carious lesions according to their depth.