Oyun Erdene Batgerel

Background/Objectives: Cone-beam computed tomography (CBCT) provides three-dimensional anatomical detail that is used when classifying impacted mandibular third molars, yet the classification performance of general-purpose multimodal artificial intelligence (AI) chatbot services in this task remains unexplored. This study compared the Winter classification performance of five general-purpose multimodal AI chatbot services with that of expert oral and maxillofacial radiologists using identical standardized CBCT-derived image composites. Methods: A total of 114 impacted mandibular third molars were retrospectively evaluated. For each tooth, a standardized composite of axial, coronal and sagittal multiplanar reconstructions together with one three-dimensional surface rendering was exported as a single JPEG image and submitted to five multimodal AI chatbot services (ChatGPT, Gemini, Copilot, Perplexity and Grok) through their web interfaces using an identical structured prompt that named the target tooth by its FDI number (38 or 48). Each impacted tooth was submitted as a separate case in a separate cleared session; a composite was never used to query two teeth simultaneously. Two board-certified oral and maxillofacial radiologists independently classified the same JPEG composites to establish an adjudicated reference standard. Accuracy, balanced accuracy, macro-averaged recall, precision and F1 score, category-level sensitivity and specificity with exact 95% confidence intervals (CIs) and Cohen’s kappa were calculated, and the accuracy of each service was compared with the majority-class (no-information) baseline. Results: The adjudicated reference standard comprised mesioangular (n = 28), distoangular (n = 9), vertical (n = 25), horizontal (n = 46) and inverted (n = 6) impactions; no transverse case occurred, so the six-category spectrum was incomplete. Inter-observer agreement between the two radiologists was 80.7% (92/114) with Cohen’s kappa 0.688 (95% CI 0.571–0.805). Accuracy was 41.2% (95% CI 32.6–50.4) for ChatGPT, 30.7% (23.0–39.7) for Copilot and 24.6% (17.6–33.2) for Gemini, Perplexity and Grok. No service exceeded the 40.4% majority-class baseline (ChatGPT versus baseline, p = 0.85). Balanced accuracy was 23.8% or lower for every service, and agreement with the reference standard was slight to none (kappa −0.003 to 0.097; all 95% CIs included zero). No service produced a correct distoangular (0/9; 95% CI 0.0–33.6) or inverted (0/6; 95% CI 0.0–45.9) classification, although these categories were represented by very few cases and the corresponding estimates are therefore highly imprecise. Conclusions: Within the specific web interfaces, prompt, image composites and testing period evaluated, general-purpose multimodal AI chatbot services did not classify impacted mandibular third molars according to the Winter system more accurately than a trivial majority-class classifier, and their agreement with an expert-adjudicated reference standard was negligible. These findings apply to the tested consumer chatbot services and to static CBCT-derived composites and should not be generalized to all multimodal AI models or to task-specific dental AI systems.

Objectives: This study aimed to compare the diagnostic behaviour and detection patterns of fourth‐ and fifth‐year dental students with those of an artificial intelligence (AI) system in identifying dental caries and restorations on panoramic radiographs within an educational framework. Methods: This retrospective cross‐sectional study included 60 anonymised panoramic radiographs comprising 1 920 individual tooth units. Diagnostic assessments were performed independently by 60 fourth‐year dental students, 60 fifth‐year dental students, and an artificial intelligence (AI) system. For each tooth, the presence or absence of caries and restorations was recorded using a standardised assessment protocol without additional calibration to reflect routine educational conditions. The AI system was used under default settings without modification of internal detection parameters. Therefore, its outputs were interpreted as threshold‐dependent diagnostic behaviour specific to the evaluated system rather than as a direct measure of diagnostic accuracy. A consensus‐based reference derived from the majority agreement of human observers was used only for contextual comparison. Statistical analyses included Kruskal–Wallis and Mann–Whitney U tests, Cohen's kappa coefficients, and Pearson's correlation analysis (α = 0.05). Results: Fourth‐ and fifth‐year students demonstrated comparable detection patterns for both caries and restorations, whereas the AI system consistently reported fewer detections per panoramic radiograph. Intergroup agreement between student groups was moderate for caries detection and higher for restoration detection, while agreement between human evaluators and the AI system was lower. The lower detection frequency of the AI system may reflect a more restrictive diagnostic threshold rather than reduced diagnostic capability. Correlation analyses revealed weak to moderate associations among evaluator groups, indicating differences in diagnostic thresholds rather than absolute diagnostic behaviour. Conclusions: Within the limitations of this study, the AI system demonstrated a distinct diagnostic behaviour pattern compared with dental students. These findings suggest that AI may serve as a complementary tool in dental education; however, its impact on learning outcomes requires further investigation through longitudinal and interventional studies.

Background: This in vitro study evaluated the effect of hydroxyapatite nanoparticle (nano-HAp) incorporation on surface roughness and Vickers hardness of a 3D-printed crown resin after thermocycling. Methods: Disk-shaped specimens (N = 84) were modified and fabricated with 0%, 1%, 2%, and 3% nano-HAp. Surface roughness (Ra) and Vickers hardness (VHN) were measured before and after thermocycling (5000 cycles). Surface morphology was qualitatively assessed using FE-SEM. Data were analyzed using two-way mixed-design ANOVA (α = 0.05). Results: Thermocycling increased surface roughness and reduced hardness in all groups. Ra values were highest in the 3% nano-HAp group after thermocycling (1.16 ± 0.47 µm). Baseline Vickers hardness differed significantly among nano-HAp concentrations, and hardness decreased after thermocycling in all groups; however, the 3% nano-HAp group exhibited the highest post-thermocycling hardness values (24.66 ± 1.51 VHN), which should be interpreted in the context of its higher baseline hardness. FE-SEM observations suggested increased surface irregularities with higher nano-HAp concentrations after thermocycling. Conclusions: Nano-HAp incorporation influenced both surface and mechanical properties, with 3% concentration showing higher hardness after aging but increased roughness.

This in vitro study evaluated the shear bond strength (SBS) of four CAD/CAM (Computer aided design/Computer aided manufacturing) polymer-based indirect composites bonded to dentin and microhybrid composite substrates using two resin cements. Gradia Plus (GP), Ceramage (Ce), Tescera ATL (TA), and Lava Ultimate (LA) were fabricated into cylindrical specimens (3 × 3 mm). Dentin substrates were obtained from extracted molars, while composite substrates were prepared from Filtek Z250 (4 mm × 2 mm). Bonding was performed using either a self-adhesive resin cement (RelyX U200; RU200) or a dual-cure adhesive resin cement (RelyX Ultimate; RU), resulting in 16 experimental groups (n = 12 per group). SBS was measured using a universal testing machine (1 mm/min), and failure modes were assessed under stereomicroscopy. Bond strength was significantly higher on composite substrates than on dentin (p < 0.001), primarily due to favorable polymer–polymer compatibility and matrix interdiffusion, which improved stress accommodation at the adhesive interface. TA and Ce showed superior adhesion when combined with RU, while LA exhibited the lowest values, particularly on dentin bonded with RU200. Overall, the dual-cure adhesive system provided stronger bonding than the self-adhesive system (p < 0.05). These findings highlight the influence of substrate type, composite architecture, and cement chemistry on interfacial performance in indirect polymer-based restorations.

Aim This study aimed to assess dentists’ knowledge, attitudes, and perceptions regarding minimally invasive dentistry (MID) and explore relationships between these factors and demographic characteristics. Material and method A cross-sectional online survey was conducted among n=114 dentists in Turkey. The questionnaire covered demographics, MID knowledge, clinical application, and perceived barriers. Data were analyzed using SPSS 27.0 with Chi-square, Mann-Whitney U, and Spearman correlation tests (p < 0.05). Results Among participants, 53.8% were female, 50% aged 20–29, and 61.5% were general dentists. Overall, 55.8% reported familiarity with MID. Knowledge increased with age and experience; 42.3% of younger dentists (20–29) had insufficient knowledge, while 72.7% of dentists aged 40+ reported good knowledge. No significant gender differences were found. Specialists, especially pediatric (80%) and restorative (66.7%) dentists, showed higher knowledge and application of MID compared to general dentists (p < 0.05). Only 25% consistently applied MID, and 42.3% applied it occasionally. The main barriers were lack of equipment (57.7%), patient expectations (21.2%), and cost (15.4%). Equipment shortage negatively correlated with MID application (r = –0.39, p < 0.05). Most participants (82.7%) expressed interest in further MID training. Conclusion Turkish dentists generally have a positive attitude toward MID, but knowledge and application vary by age and specialty. Younger general dentists show lower knowledge and use, while specialists demonstrate greater awareness and implementation. Addressing equipment shortages and enhancing training opportunities, especially for younger dentists, are essential to promote wider MID adoption.

Amaç: Bu kesitsel çalışmada, farklı sınıflardaki dişhekimliği öğrencileri arasında dental anksiyete düzeyi değerlendirildi ve dental anksiyete seviyesinin travmatik dental geçmiş ile bağlantısı olup olmadığı irdelendi. Yöntem: 27 Şubat-27 Mart 2023 tarihleri arasında Biruni Üniversitesi Diş Hekimliği Fakültesi’ndeki dördüncü ve beşinci sınıf öğrencilerinin katıldığı çalışmada her iki sınıftan eşit sayıda (n=300) öğrenciye yer verildi ve toplamda 300 öğrenci ile çalışma gerçekleştirildi. Dijital ortamda hazırlanan anket formları iki kısım halinde oluşturuldu. Formun ilk kısmında sosyodemografik verilerin ve travmatik dental deneyim geçmişinin tespitine yönelik sorular bulunurken; ikinci kısımda dental anksiyete seviyesini ölçen skala yer aldı. Dental anksiyete seviyeleri Modifiye Dental Anksiyete Skalası (MDAS) ile ölçüldü ve yüksek dental anksiyeteyi belirlemek üzere cut-off değeri ≥13 olarak belirlendi. Veriler analiz edilirken Mann Whitney U ve Ki-Kare testlerinden faydalanıldı. Bulgular: Kadınların MDAS skorları 8,57±2,76 erkeklere göre 7,84±2,88 daha yüksek bulundu (p