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.
OBJECTIVE: This paper highlights the similarities and differences among these cell subpopulations, particularly between intraoral fibroblasts (human periodontal ligament, gingival and oral mucosa fibroblasts) and dermal fibroblasts based on several factors including their morphology, growth and proliferation rate.
RESULTS: It could be suggested that each subpopulation of fibroblasts demonstrate different positionspecified gene signatures and responses towards extracellular signals. These dissimilarities are crucial to be taken into consideration to employ specific methodologies in stimulating these cells in vivo.
CONCLUSION: A comparison of the characteristics of these cell subpopulations is desired for identifying appropriate cellular applications.
MATERIALS AND METHODS: Sixteen individuals with a range of oral potentially malignant disorders (OPMD) and normal oral mucosa were included. Five areas of the oral cavity were photographed by three dentists using mobile phone cameras with 5 MP-13 MP resolutions. On the same day, the patients were given COE by two oral medicine specialists (OMS) and 3 weeks later, they reviewed the images taken using the phone, and concordance was examined between the two by Kappa statistics. The sensitivity and specificity of clinical diagnosis using the phone images were also measured. Pre- and post-program questionnaires were answered by both the dentists and the OMS to determine the feasibility of integrating teledentistry in their clinical practice.
RESULTS: The Kappa values in determining the presence of lesion, category of lesion (OPMD or not), and making referral decision were moderate to strong (0.64-1.00). The overall sensitivity was more than 70% and specificity was 100%. The false negative rate decreased as the camera resolution increased. All dentists agreed that the process could facilitate early detection of oral mucosal lesion, and was easy to use in the clinic.
CONCLUSIONS: This study provides evidence that teledentistry can be used for communication between primary care and OMS and could be readily integrated into clinical setting for patient management.
OBJECTIVES: To assess the effectiveness of school dental screening programmes on overall oral health status and use of dental services.
SEARCH METHODS: Cochrane Oral Health's Information Specialist searched the following databases: Cochrane Oral Health's Trials Register (to 4 March 2019), the Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Register of Studies, to 4 March 2019), MEDLINE Ovid (1946 to 4 March 2019), and Embase Ovid (15 September 2016 to 4 March 2019). The US National Institutes of Health Trials Registry (ClinicalTrials.gov) and the World Health Organization International Clinical Trials Registry Platform were searched for ongoing trials. No restrictions were placed on language or publication status when searching the electronic databases; however, the search of Embase was restricted to the last six months due to the Cochrane Centralised Search Project to identify all clinical trials and add them to CENTRAL.
SELECTION CRITERIA: We included randomised controlled trials (RCTs) (cluster or parallel) that evaluated school dental screening compared with no intervention or with one type of screening compared with another.
DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane.
MAIN RESULTS: We included seven trials (five were cluster-RCTs) with 20,192 children who were 4 to 15 years of age. Trials assessed follow-up periods of three to eight months. Four trials were conducted in the UK, two were based in India and one in the USA. We assessed two trials to be at low risk of bias, two trials to be at high risk of bias and three trials to be at unclear risk of bias.None of the trials had long-term follow-up to ascertain the lasting effects of school dental screening.None of the trials reported the proportion of children with untreated caries or other oral diseases, cost effectiveness or adverse events.Four trials evaluated traditional screening versus no screening. We performed a meta-analysis for the outcome 'dental attendance' and found an inconclusive result with high heterogeneity. The heterogeneity was found to be, in part, due to study design (three cluster-RCTs and one individual-level RCT). Due to the inconsistency, we downgraded the evidence to 'very low certainty' and are unable to draw conclusions about this comparison.Two cluster-RCTs (both four-arm trials) evaluated criteria-based screening versus no screening and showed a pooled effect estimate of RR 1.07 (95% CI 0.99 to 1.16), suggesting a possible benefit for screening (low-certainty evidence). There was no evidence of a difference when criteria-based screening was compared to traditional screening (RR 1.01, 95% CI 0.94 to 1.08) (very low-certainty evidence).In one trial, a specific (personalised) referral letter was compared to a non-specific one. Results favoured the specific referral letter with an effect estimate of RR 1.39 (95% CI 1.09 to 1.77) for attendance at general dentist services and effect estimate of RR 1.90 (95% CI 1.18 to 3.06) for attendance at specialist orthodontist services (low-certainty evidence).One trial compared screening supplemented with motivation to screening alone. Dental attendance was more likely after screening supplemented with motivation, with an effect estimate of RR 3.08 (95% CI 2.57 to 3.71) (low-certainty evidence).Only one trial reported the proportion of children with treated dental caries. This trial evaluated a post screening referral letter based on the common-sense model of self-regulation (a theoretical framework that explains how people understand and respond to threats to their health), with or without a dental information guide, compared to a standard referral letter. The findings were inconclusive. Due to high risk of bias, indirectness and imprecision, we assessed the evidence as very low certainty.
AUTHORS' CONCLUSIONS: The trials included in this review evaluated short-term effects of screening. We found very low-certainty evidence that is insufficient to allow us to draw conclusions about whether there is a role for traditional school dental screening in improving dental attendance. For criteria-based screening, we found low-certainty evidence that it may improve dental attendance when compared to no screening. However, when compared to traditional screening, there is no evidence of a difference in dental attendance (very low-certainty evidence).We found low-certainty evidence to conclude that personalised or specific referral letters may improve dental attendance when compared to non-specific counterparts. We also found low-certainty evidence that screening supplemented with motivation (oral health education and offer of free treatment) may improve dental attendance in comparison to screening alone. For children requiring treatment, we found very-low certainty evidence that was inconclusive regarding whether or not a referral letter based on the 'common-sense model of self-regulation' was better than a standard referral letter.We did not find any trials addressing possible adverse effects of school dental screening or evaluating its effectiveness for improving oral health.