Purpose: This review aimed to explore the scientific literature concerning the methodologies and applications ofartificial intelligence (AI) in the field of endodontics. The findings may equip dentists with the necessary technicalknowledge to understand the opportunities presented by AI. Materials and Methods: Articles published between 1992 and 2023 were retrieved through an electronic search of Medline via the PubMed, Scopus, and Google Scholar databases. The search, which was limited to articles publishedin English, aimed to identify relevant studies by employing the following keywords: “artificial intelligence,” “machine learning,” “deep learning,” “endodontic,” “root canal treatment,” and “radiography.” Ultimately, 71 studies thataddressed the application of AI in endodontics were selected. Results: Numerous studies have demonstrated the effectiveness of AI applications in endodontics. These usesencompass the identification of root fractures and periapical lesions, assessment of working length, investigation ofroot canal system anatomy, prediction of retreatment success, and evaluation of dental pulp stem cell viability. Conclusion AI technology is poised to advance aspects of endodontics including scheduling, patient care, management of drug-drug interactions, prognostic diagnosis, and the emerging area of robotic endodontic surgery.AI methods have demonstrated accuracy and precision in the identification, assessment, and prediction of diseases.Thus, AI can significantly improve endodontic diagnosis and treatment, increasing the overall efficacy of endodontictherapy.

Purpose: This review aimed to explore the scientific literature concerning the methodologies and applications ofartificial intelligence (AI) in the field of endodontics. The findings may equip dentists with the necessary technicalknowledge to understand the opportunities presented by AI. Materials and Methods: Articles published between 1992 and 2023 were retrieved through an electronic search of Medline via the PubMed, Scopus, and Google Scholar databases. The search, which was limited to articles publishedin English, aimed to identify relevant studies by employing the following keywords: “artificial intelligence,” “machine learning,” “deep learning,” “endodontic,” “root canal treatment,” and “radiography.” Ultimately, 71 studies thataddressed the application of AI in endodontics were selected. Results: Numerous studies have demonstrated the effectiveness of AI applications in endodontics. These usesencompass the identification of root fractures and periapical lesions, assessment of working length, investigation ofroot canal system anatomy, prediction of retreatment success, and evaluation of dental pulp stem cell viability. Conclusion AI technology is poised to advance aspects of endodontics including scheduling, patient care, management of drug-drug interactions, prognostic diagnosis, and the emerging area of robotic endodontic surgery.AI methods have demonstrated accuracy and precision in the identification, assessment, and prediction of diseases.Thus, AI can significantly improve endodontic diagnosis and treatment, increasing the overall efficacy of endodontictherapy.

Purpose: This review aimed to explore the scientific literature concerning the methodologies and applications ofartificial intelligence (AI) in the field of endodontics. The findings may equip dentists with the necessary technicalknowledge to understand the opportunities presented by AI. Materials and Methods: Articles published between 1992 and 2023 were retrieved through an electronic search of Medline via the PubMed, Scopus, and Google Scholar databases. The search, which was limited to articles publishedin English, aimed to identify relevant studies by employing the following keywords: “artificial intelligence,” “machine learning,” “deep learning,” “endodontic,” “root canal treatment,” and “radiography.” Ultimately, 71 studies thataddressed the application of AI in endodontics were selected. Results: Numerous studies have demonstrated the effectiveness of AI applications in endodontics. These usesencompass the identification of root fractures and periapical lesions, assessment of working length, investigation ofroot canal system anatomy, prediction of retreatment success, and evaluation of dental pulp stem cell viability. Conclusion AI technology is poised to advance aspects of endodontics including scheduling, patient care, management of drug-drug interactions, prognostic diagnosis, and the emerging area of robotic endodontic surgery.AI methods have demonstrated accuracy and precision in the identification, assessment, and prediction of diseases.Thus, AI can significantly improve endodontic diagnosis and treatment, increasing the overall efficacy of endodontictherapy.