This study aimed to evaluate the impact of MeSH based personalized learning guides generated by ChatGPT-4o on the radiographic diagnostic performance of dental students and to compare it with the traditional correct/incorrect feedback method. This randomized controlled study was conducted among fifth-year dental students at Afyonkarahisar Health Sciences University. A total of 110 students were randomly assigned to either the experimental or control group. The experimental group received personalized study guides targeting their learning gaps, generated by ChatGPT-4o based on Medical Subject Headings (MeSH). The control group received only a standard correct/incorrect feedback analysis. One month after the intervention, a post-test was administered to assess diagnostic accuracy and student satisfaction. The increase in test scores from pre- to post-test was significantly higher in the experimental group (3.6 ± 1.0) compared to the control group (1.3 ± 1.2; p < 0.001). Final test scores were also significantly higher in the experimental group (p < 0.001). Survey responses indicated that the experimental group rated the feedback as more understandable, beneficial, and motivating compared to the control group. ChatGPT-4o based personalized feedback proved to be an effective tool for enhancing diagnostic performance and supporting learning in dental education. The findings suggest that AI-driven individualized educational strategies hold significant potential in the future of dental training.

Objective: This study aimed to evaluate the awareness levels of actively practicing dentists in Türkiye regarding artificial intelligence (AI)-related ethical issues, data security, anonymization, and legal regulations. Materials and methods: A cross-sectional online survey (Google Forms) used a 12-item questionnaire (4 demographics; 8 awareness domains) rated on a five-point Likert scale. Participants were recruited via snowball sampling. Descriptive statistics, independent-samples t-tests, and one-way analysis of variance with Tukey post hoc tests were applied (p < 0.05). Results: A total of 257 dentists participated. Mean domain scores ranged from 2.97 to 3.13; awareness of ethical issues was highest (3.13 ± 1.44) and perception of encryption lowest (2.97 ± 1.45). No significant gender differences were observed. University hospital dentists reported significantly higher awareness of ethical issues and a greater perceived need for anonymization than other institution types (p < 0.05). For awareness of Personal Data Protection Law (KVKK), scores were higher in university hospitals and private dental polyclinics than in private practices and public hospitals (p < 0.05). Professional experience was associated with differences in perception of encryption, awareness of personal data protection law, awareness of ethical issues, and perceived AI ethical risks (p < 0.05); perception of data security and awareness of big data security did not differ significantly (p > 0.05). Conclusion: Dentists demonstrated varying levels of awareness across domains, with higher awareness reported in academic settings. Experience-related patterns differed by domain, indicating the need for focused educational strategies addressing legal and ethical aspects of AI-supported dental practice.

The aim of this study was to evaluate the trabecular structure of the alveolar bone in individuals with mandibular second premolar hypodontia using fractal

Aim: Panoramic radiography is frequently used in dental practice as an imaging technique that provides an extensive view of facial anatomical structures. Achieving high-quality radiographic images requires precise positioning and technique. This study aims to evaluate the quality of panoramic radiographs, to identify common errors that compromise diagnostic adequacy, and to analyze interobserver agreement levels concerning these errors. Material and Method: A study analyzed 947 panoramic radiographs from the archive of Ordu University based on nine specific error criteria. Four research assistants evaluated the diagnostic quality of each image, classifying them as “excellent,” “diagnostically acceptable,” or “unacceptable.” Inter-observer agreement was measured with kappa statistics, and overall agreement was evaluated using the Fleiss κ test. Results: The rate of incorrect radiographs was 66.1% to 78.8%, with the most common error criterion differing for each observer. The least common error was the chin tipped too low for observers 1 and 2, and the patient positioned forward for observers 3 and 4. The highest inter-observer agreement was observed regarding the presence of foreign objects on the radiographs, while the lowest agreement occurred in cases where the patient was positioned too far back. Overall, the diagnostic quality of the panoramic radiographs was rated as “acceptable,” with scores ranging from 60.5% to 69.5%. The Fleiss Kappa analysis indicated fair agreement among the four observers in assessing radiographic quality (k=0.252). Conclusion: This study demonstrates that errors in panoramic radiography significantly impact image quality and diagnostic accuracy, highlighting the need for standardization, the use of various imaging models, and enhanced training in radiographic education.