Artificial Intelligence in Detecting Peri Apical Lesion: A systematic review

Abstract

Objective: Artificial intelligence plays a very important role in diagnosis and treatment planning in dentistry. The aim of this systematic review is to analyze the accuracy of artificial intelligence in detecting periapical lesions in endodontics. Material and Methods: Using the MeSH keywords: Artificial intelligence (AI), AI in endodontics, neural networks and endodontics, machine learning, deep neural network and periapical lesion, AI dental imaging, and AI treatment diagnosis and endodontics electronic search was performed in four databases - PubMed/Medline (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics). The English language articles reporting on AI in different dental specialities were screened for eligibility and chosen for analysis based on set inclusion criteria. Results: A total of seven full-text articles were selected and systematically analysed. Artificial intelligence technology was found to have greater accuracy in detecting periapical lesions when compared to clinicians. Conclusion: Artificial intelligence is a reliable tool in the diagnosis of periapical lesions in endodontics, with the use of which accuracy and precision of diagnosis can be enhanced.