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ObjectiveTo assess the efficacy of a “teledentistry” method using a mobile app (Telesmile) in enhancing knowledge of oral health conditions and oral hygiene practices among the blind and deaf populations in Jazan Province in Saudi Arabia.MethodsA randomized parallel design controlled study was conducted among 50 blind and 50 deaf subjects between the ages of 12–18 years, randomly chosen from blind and deaf schools. The participants were selected based on the inclusion and exclusion criteria. An innovative teledentistry platform named Telesmile, a mobile application for the Apple iOS App Store and Google Play Store, was developed. Multimedia Arabic dental sign language oral hygiene instructional videos were created and uploaded in the Telesmile mobile application under the deaf category. Similarly, oral hygiene instructions were audio recorded by experts and uploaded under the blind category in the Telesmile mobile application. Group I of the blind (n = 25) and deaf participants (n = 25) received regular oral hygiene instructions while Group II of the blind (n = 25) and deaf (n = 25) participants received the Telesmile mobile application intervention. The knowledge of the participants pertaining to oral health and oral hygiene practices was evaluated using a close-ended questionnaire comprising 14 questions at the initial visit (T0). Training sessions were conducted for all participants and the Telesmile mobile application was distributed among the participants in Group II. After 4 weeks (T1), the knowledge of the participants regarding oral health and hygiene practice was re-evaluated and compared between each group.ResultsThe chi-square test revealed that the marginal mean of the knowledge of the blind and deaf participants pertaining to oral health and oral hygiene practices was very poor at their initial visit (T0) and it significantly increased (p

Background and Objectives: Gingival recession results in adverse aesthetics and root sensitivity, and there is a need to treat and prevent its further progression. To overcome these problems, various advances have been made by clinicians in treating gingival recession based on the type of gingival recession. Miller’s classification has been used for a long time to classify the type of recession. However, certain limitations have been found with use of Miller’s classification such as a lack of clarity in the method for measuring soft and hard tissue loss in the interproximal area. Cairo classification was proposed to overcome limitations of Miller’s classification to classify gingival recession. Cairo’s classification is a treatment-oriented classification based on buccal and interproximal attachment loss. Therefore, the study was conducted to assess and compare the reliability of Miller’s and Cairo’s classifications in determining gingival recession. Material and methods: A total of 220 buccal gingival recession defects were included in the study based on the inclusion and exclusion criteria. Four examiners were included in the study. Two examiners classified the recession defects according to Miller’s classification and the other two examiners classified recession defects according to Cairo’s classification at baseline and at a 1-week interval. Statistical analysis was conducted using SPSS software version 25.0 using Cohen’s kappa correlation coefficient and Chi-square test statistics to determine the intra- and inter-rater agreement among the examiners for the two gingival recession classification systems. A p value of Results: The intra-rater agreement for Cairo’s classification was 0.86 and 0.82, whereas for Miller’s classification, it was found to be 0.68. The inter-rater reliability agreement for Cairo’s classification was 0.82 and 0.8, whereas for the Miller’s classification, it was 0.56 and 0.67. Conclusions: Within the limitations of the study, it was found that Cairo’s classification is clearer and more reliable than Miller’s classification in the assessment of gingival recession.

In the global epidemic era, oral problems significantly impact a major population of children. The key to a child’s optimal health is early diagnosis, prevention, and treatment of these disorders. In recent years, the field of artificial intelligence (AI) has seen tremendous pace and progress. As a result, AI’s infiltration is witnessed even in those areas that were traditionally thought to be best left to human specialists. The ultimate ability to improve patient care and make precise diagnoses of illnesses has revolutionized the world of healthcare. In the field of dentistry, the competence to execute treatment measures while still providing appropriate patient behavior counseling is in high demand, particularly in the field of pediatric dental care. As a result, we decided to conduct this review specifically to examine the applications of AI models in pediatric dentistry. A comprehensive search of the subjects was done using a wide range of databases to look for studies that have been published in peer-reviewed journals from its inception until 31 December 2022. After the application of the criteria, only 25 of the 351 articles were taken into consideration for this review. According to the literature, AI is frequently used in pediatric dentistry for the purpose of making an accurate diagnosis and assisting clinicians, dentists, and pediatric dentists in clinical decision making, developing preventive strategies, and establishing an appropriate treatment plan.