Materials and Methods: Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted.
Results: The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics.
Conclusion: The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.
Results: A total of 506 dental professionals participated in the study with the response rate of 89.39%. More than half of the participants (50-75%) endorsed that teledentistry is a useful tool for improving clinical practice as well as patient care. Two-thirds of the participants (69.96%) considered that teledentistry would reduce cost for the dental practices. On the other hand, about 50-70% of dental professionals expressed their concerns regarding the security of the data and consent of patients. The most preferred communication tool for teledentistry was reported to be videoconference followed by phone. The majority of participants recommended the use of teledentistry in the specialty of oral medicine, operative dentistry, and periodontics. There was a significant difference between the age, experience of dentists, and their qualifications with domains of teledentistry.
Conclusions: The overall impact of dental professionals towards teledentistry was positive with adequate willingness to incorporate this modality in their clinical practice. However, the perceived concerns pertaining to teledentistry are significant impediments towards its integration within the oral health system. An in-depth study of its business model and cost-benefit needs of time, especially in the context of developing countries, in order to avail the optimum benefits of teledentistry.