Diagnostic accuracy of artificial intelligence versus dental experts in predicting endodontic outcomes: A systematic review - Sahil Choudhari; Sindhu Ramesh; Tanvi Deepak Shah; Kavalipurapu Venkata Teja (Wolters Kluwer Medknow Publications, 2024)
Introduction: In the rapidly evolving landscape of health care, artificial intelligence (AI) has emerged as a promising tool to enhance diagnostic accuracy across various medical disciplines. Within the realm of dentistry, one critical area of focus is endodontics, which involves the diagnosis and treatment of dental pulp diseases. This systematic review investigates the diagnostic precision of AI in contrast to dental experts when predicting endodontic outcomes. Materials and Methods: The review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The review was registered on the Open Science Framework database. A systematic search was performed of the literature on the application of AI versus dental experts in endodontics. The search was conducted on PubMed, Scopus, Web of Science, and OVID until December 2022. The QUADAS-2 tool was used to evaluate the risk of bias. Results: The initial search retrieved 972 records, of which eight articles were included in the study. The studies reported application of AI for working length determination, periapical lesions, pulp and tooth segmentation, apical periodontitis, vertical root fracture, and C-shaped canals. QUADAS-2 tool revealed a low risk of bias in five out of the eight included studies. Conclusion: AI models demonstrated a notable increase in accuracy and effectiveness in endodontic diagnosis and treatment planning. These results suggest that the integration of AI technology in endodontic diagnosis and treatment planning has immense potential to serve as a promising aid.