Hyperdontia can cause numerous aesthetic and functional problems. The diagnosis is made radiologically, and the most commonly used radiological method is orthopantomography, while CBCT is also used. CBCT has the advantage of being three-dimensional. Artificial Intelligence is widely used in medicine and dentistry, and it can create a specific algorithm to aid in diagnosis and suggest therapeutic procedures. In a case report, a 6-year-old boy was diagnosed with a supernumerary tooth between the upper central incisors. Orthopantomography revealed another impacted supernumerary tooth, and the patient was referred for CBCT. A platform for analyzing dental images, based on artificial intelligence, Diagnocat (Diagnocat Inc., San Francisco, CA, USA), was used for analysis and the AI system identified the supernumerary teeth and provided a complete plan for treatment. The use of AI in dentistry allows for faster and more accurate diagnosis and treatment planning.

The aim of this study was to determine the impact of oral health on adolescent quality of life and to compare the results obtained using standard statistical methods and artificial intelligence algorithms. In order to measure the impact of oral health on adolescent quality of life, a validated Serbian version of the Oral Impacts on Daily Performance (OIDP) scale was used. The total sample comprised 374 respondents. The obtained results were processed using standard statistical methods and machine learning, i.e., artificial intelligence algorithms—singular value decomposition. OIDP score was dichotomized into two categories depending on whether the respondents had or did not have oral or teeth problems affecting their life quality. Human intuition and machine algorithms came to the same conclusion on how the respondents should be divided. As such, method quality and the need to perform analyses of this type in dentistry studies were demonstrated. Using artificial intelligence algorithms, the respondents can be clustered into characteristic groups that allow the discovery of details not possible with the intuitive division of respondents by gender.

Wood–plastic composites (WPCs) are some of the most common modern composite materials for interior and exterior design that combine natural waste wood properties and the molding possibility of a thermoplastic polymer binder. The addition of reinforcing elements, binding agents, pigments, and coatings, as well as changes to the microstructure and composition, can all affect the quality of WPCs for particular purposes. To improve the properties, hybrid composite panels of WPCs with 30 wt. % and 40 wt. % of wood content and reinforced with one or three metal grid layers were prepared sequentially by extrusion and hot pressure molding. The results show an average 20% higher moisture absorption for composites with higher wood content. A high impact test (HIT) revealed that the absorbed energy of deformation increased with the number of metal grid layers, regardless of the wood content, around two times for all samples before water immersion and around ten times after water absorption. Also, absorbed energy increases with raised wood content, which is most pronounced in three-metal-grid samples, from 21 J to 26 J (before swelling) and from 15 J to 24 J (after swelling). Flexural tests follow the trends observed by HIT, indicating around 65% higher strength for samples with three metal grid layers vs. samples without a metal grid before water immersion and around 80% higher strength for samples with three metal grid layers vs. samples without a grid after water absorption. The synthesis route, double reinforcing (wood and metal), applied methods of characterization, and optimization according to the obtained results provide a WPC with improved mechanical properties ready for an outdoor purpose.

Dental students are an interesting population because they are expected to have a higher level of knowledge of and to exhibit better oral hygiene habits, and thus have a greater impact on the environment, families, and society as a whole. The aim of this research was to determine the state of oral hygiene in dental students before and after the interventional health education program. The research sample consisted of 119 students of dentistry in their first and fourth years of study. The first research stage was conducted before health education intervention (for the evaluation of selected oral health parameters, the Decayed, Missing and Filled index, Greene–Vermillion index, Silness–Löe plaque index, Silness–Löe gingival index, and the Community Periodontal Index of Treatment Needs index were used). The second stage was conducted as a clinical measurement of oral health changes. The conducted health education intervention, to an extent, led to changes in the state of oral hygiene among the students, and thus healthier habits. There was a statistically significant difference in the examined population between the beginning of the study and after the health education intervention program. Although a significant improvement in oral hygiene and oral health was noticed after the health education intervention program, the state of oral hygiene was still not at a satisfactory level among the dental students, contrary to our expectations.

Background/Objectives: Behavior management is a major challenge in pediatric dentistry, particularly during the first dental visit, when anxiety, fear, and negative expectations can compromise cooperation and clinical outcomes. While evidence-based behavior guidance techniques are well established, their effectiveness depends on early identification of behavioral risk and individualized planning. This study aimed to develop and clinically evaluate a parent-completed digital pre-visit tool to support individualized behavior management and targeted use of digital distraction in pediatric dentistry. Methods: A web-based application was developed using HTML, CSS, and JavaScript. It was applied to a prospective observational cohort of 90 pediatric patients aged 4–8 years (mean 6.1 ± 1.2), including 48 girls and 42 boys. Parents completed a pre-visit questionnaire covering four domains: child’s age, previous dental experiences, reactions to unfamiliar situations, and individual interests, including stimuli to avoid. Based on predefined decision rules, the tool generated recommended clinical approaches, including behavior guidance techniques, digital distraction, and inhalation sedation. Results: Over 90% of children were successfully managed during their first visit. Children in low- and moderate-risk groups had significantly higher odds of treatment success compared to high-risk children. Low-risk children almost universally completed treatment at the first visit, while a substantial portion of moderate-risk children were successfully managed without an adaptation visit. Digital distraction, particularly when tailored to individual interests, enhanced cooperation and tolerance of procedures. Conclusions: The digital pre-visit tool enables early identification of behavioral risk and supports targeted application of digital distraction and sedation. This approach can improve child cooperation, reduce anxiety, optimize clinical efficiency, and contribute to positive early dental experiences.