Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI techniques. We evaluated 40 studies from the past 23 years, carefully selected for their relevance and quality. Our analysis highlights the potential of AI, especially convolutional neural networks (CNNs), to improve diagnostic accuracy and efficiency in detecting dental caries. The findings underscore the transformative potential of AI in clinical dental practice.

Background. Detachment of acrylic teeth from denture base material is a common complication in dentistry which accounts for 26–30% of repair cases. This study aimed to evaluate the effect of alumina-blasting, silane coupling agent, and thermal cycling on the shear bond strength of repaired teeth to denture base. Materials and Methods. Specimens (140) of repaired teeth to denture bases were fabricated and divided into 14 groups: 7 groups before thermal cycling and 7 groups after thermal cycling (n = 10). The groups were divided according to surface treatment into no treatment (control), treatment of the base (B), the tooth (T), or both (BT). Each group was further subdivided according to the surface treatment method into alumina-blasting or alumina-blasting and silane coupling agent. After treatment, acrylic discs and teeth were fixed in a jig, and the repair procedure was done. Half the specimens were thermally cycled. Shear bond strength was measured using a universal testing machine. ANOVA and Tukey HSD tests were performed at α = 0.05. Results. Surface treatment significantly improved the bond strength compared to the control group . Comparing surface treatments, alumina-blasting with silane coupling agent treatment resulted in significantly higher strength compared to alumina-blasting alone . The BT group treated with alumina-blasting and silane coupling agent showed the highest significant shear bond strength (23.91 ± 0.96 MPa) . Significant drop in strength value was observed in all groups after thermal cycling except the BT group treated with alumina-blasting . Conclusion. Surface treatment using alumina-blasting with silane coupling agent for denture base and tooth increased repair strength.

Phonetics plays a major role in the fabrication of prostheses. This study aimed to assess the knowledge of students regarding the role of phonetics in denture fabrication and to improve the educational process and the clinical application. The study was conducted at the College of Dentistry, Imam Abdulrahman Bin Faisal University, and involved a survey of 344 dental students and interns. The questionnaire contained 20 questions and was divided into three sections: general knowledge, clinical correlations, and clinical evaluations. The data were collected and analyzed statistically using independent t-tests, one-way ANOVA, and Tukey’s post hoc tests. The response rate was 100%. Male and female students only differed significantly in terms of their scores for answers to general knowledge questions, with females achieving better results (p = 0.023). General knowledge varied significantly between fourth-year students and all other levels (p < 0.001), and fifth-year students and interns (p = 0.027). The clinical correlations varied significantly between fourth-year students and interns (p = 0.01), whereas the clinical evaluations varied between all the academic years and interns (fourth-year, p < 0.001; fifth-year, p = 0.003; and sixth-year, p = 0.017). The interns obtained the highest scores in all sections. There was a lack of awareness among dental students of some aspects of the role of phonetics in denture fabrication. The study highlights the deficiencies that need to be addressed and the need for adjustments to the curriculum related to removable prosthodontics in order to improve the knowledge of students regarding the role of speech in denture fabrication.