Bahadır, Hasibe SevilayKeskin, Neslihan BüşraKurşun Çakmak, Emine ŞebnemGüneç, GürkanCesur Aydın, KaderPeker, Fatih2025-08-292025-08-292025Bahadır, H. S., Keskin, N. B., Kurşun Çakmak, E. Ş., Güneç, G., Cesur Aydın, K. ve Peker, F. (2025). Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists. Oral Radiology, 41(1), 52-59. http://dx.doi.org/10.1007/s11282-024-00775-10911-60281613-9674http://dx.doi.org/10.1007/s11282-024-00775-1https://hdl.handle.net/20.500.12511/13042Objectives: This study intended to evaluate patients’ attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists. Methods: A total of 272 completed questionnaires were included in this study. In the first part of the study, approval was obtained from the patients, and data were collected about their socio-demographic characteristics. In the second part the 11-item Dentist Trust Scale was applied. In the third and fourth parts, there were questions about two clinical scenarios, the patients’ knowledge of attitudes toward AI, and how the AI-based diagnosis had affected their trust. Evaluation was performed using a Likert-type scale. Data were analyzed with the Chi-square, one-way ANOVA, and ordinal logistic regression tests (p < 0.05). Results: The patients believed that “AI is useful” (3.86 ± 1.03) and were not afraid of the use of AI in dentistry (2.40 ± 1.05). Educational level was considerably related to the patients’ attitudes to the use of AI for dental diagnostics (p < 0.05). The patients stated that “dentists are extremely thorough and careful” (4.39 ± 0.77). Conclusions: The patients displayed a positive attitude to AI-based diagnosis in the dental field and appear to exhibit trust in dentists. The use of Al in routine clinical practice can provide important benefit to physicians as a clinical decision support system in dentistry and understanding patients’ attitudes may allow dentists to shape AI-supported dentistry in the future.eninfo:eu-repo/semantics/embargoedAccessArtificial IntelligenceCommunicationDentist TrustDiagnosisMachine LearningPatientsArticle411525910.1007/s11282-024-00775-1Q3WOS:0013312457000012-s2.0-8520575629039379636Q2