Dental Caries is defined as an irreversible microbial disease of the calcified tissue of teeth characterized by demineralization of the inorganic part and destruction of organic substance of the tooth which leads to cavitation [1]. Dental caries is the most prevalent dental disease worldwide. According to Global Burden Diseases 2017, most common health condition in permanent teeth is untreated dental caries [2]. The visual-tactile method is most commonly used technique in diagnosis of dental caries whereas in radiography bitewing radiography is most common [3]. Accuracy of early diagnosis of dental caries is still a challenging problem for dentists. Neural networks and artificial intelligence (AI) are increasingly being used in the field of dentistry.  AI technology has a possibility of improving patient care through better diagnostic aids and reduced errors in daily practice [4].

Artificial intelligence is defined as the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages [5]. Convolutional Neural Network (CNN) is a tool of artificial intelligence for effective analysis of images (Figure 1) [6]. Several limitations exist in healthcare like serious diagnostic errors, mistakes in treatment, an enormous waste of resources, inefficiencies in workflow, inequities, and inadequate time between patients and clinicians [7,8].  Leaders in healthcare and computer scientists have asserted that AI might have a role in addressing all these problems [9]. It has been estimated that, per day, AI would process over 250 million images for the cost of about $1,000 [10]. Artificial intelligence will be used in augmented reality for future remote eHealth [11,12].