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Öğe Comparison of diagnoses made by dentistry students and by artificial intelligence dentists(2025) Bahadır, Hasibe Sevilay; Keskin, Neslihan Büşra; Kurşun Çakmak, Emine Şebnem; Güneç, Gürkan; Cesur Aydın, Kader; Sarı, Saliha KübraObjectives: The introduction of artificial intelligence (AI) about great changes in the field of dentistry, but it has not yet been fully determined in which areas it will make a positive contribution to dentistry students. The objective of our study was to compare the diagnostic accuracy of undergraduate students (fourth-year dentistry students [4DS] and final-year dentistry students [5DS]) and AI when examining panoramic radiographs. Methods: Fifty panoramic radiographs and 1602 teeth were examined by 50 4DS who had not received a clinical practice internship, 50 5DS, and an AI application. The participants and the AI application evaluated the teeth seen in each radiograph one by one in terms of caries, fillings, teeth with root canal treatment, periodontal loss, extractions, crowns, teeth with apical lesions, and impacted and extracted teeth. Findings were recorded in an Excel chart. Chi-square analysis was used to compare diagnostic success between the groups. Results: The results indicate that there was a statistically significant difference in the identified accuracy of caries, fillings, and extractions between the AI application and undergraduate students (p < 0.05). Although AI showed more identified accuracy in teeth with apical lesions, impacted teeth, and teeth with root canal treatment than in undergraduate students, there was no significant difference between them (p > 0.05). Conclusion: AI exhibited better results than undergraduate students especially in the detection of caries and fillings. AI could improve undergraduates’ accuracy in detecting caries, fillings, and extractions and help them make accurate treatment decisions. In cases where dentistry students are examining patients using panoramic radiographs, employing AI programs during their clinical training to confirm and strengthen the student's diagnosis may be a promising new development.Öğe Impact of COVID-19 pandemic on continuing professional development of endodontists: A comprehensive survey study(Türkiye Klinikleri, 2022) Uslu, Gülşah; Özyürek, Taha; Kayahan, Mehmet Baybora; Gündoğar, Mustafa; Keskin, Neslihan BüşraObjective: Continuing professional development (CPD) is a lifelong process that continues despite all kinds of obstacles. The aim of this study was to evaluate of endodontists’ attitudes towards CPD during the coronavirus disease-2019 pandemic and online educa tional resources (OERs). Material and Methods: A questionnaire on demographic data and preferred resources before and after the pan demic was sent to 554 potential participants via e-mail. A chi-square test and multivariate logistic regression test were conducted on the ob tained data at a 5% significance level. Results: One hundred seventy five participants responded to the survey. Of all the participants, 67% were women and 45% were academicians. Since the pandemic began, OERs have been preferred over traditional resources, but traditional ones were considered more useful than OERs. Most of the respondents believed that contagion concerns represented the greatest obstacle to CPD. Gender and experience were related to the perception that the pandemic affected the respondents’ CPD activities (p<0.001). Spe cialty/PhD students tended to benefit more than others from OERs (p<0.05). The respondents mostly considered that OERs are comfort able and advantageous in terms of time, cost, professional knowledge and skill. Conclusion: The resources endodontists chose for CPD ac tivities seemed to have changed in favour of OERs during the pandemic despite their lower perceived usefulness as compared with traditional resources.Öğe Investigation of the effectiveness of sonic, ultrasonic and new laser-assisted irrigation activation methods on smear removal and tubular penetration(Springer Science and Business Media Deutschland GmbH, 2023) Uslu, Gülşah; Gündoğar, Mustafa; Üngör, Mete; Özyürek, Taha; Erkan, Erhan; Keskin, Neslihan BüşraThe aim of this study was to examine the effectiveness of different irrigation activation methods on smear layer removal and tubular penetration. One hundred-five distal roots of mandibular molar teeth in total; 50 for smear removal efficiency (n = 10) analysis using scanning electron microscopy (SEM), and 55 roots were used to examine tubular penetration using confocal laser scanning microscope (CLSM). Five different irrigation activation methods were used in this study; conventional needle irrigation (CNI), sonic irrigation device of EDDY, passive ultrasonic irrigation (PUI), PIPS and SWEEPS techniques, which are two different laser irrigation activation methods. The obtained data were statistically analyzed and the significance level was determined as p < 0.05. At the apical level, the cleanest canal walls were observed when laser methods PIPS and SWEEPS were used, while in the middle third, there was no difference in smear removal efficiencies between all groups except for the CNI (p > 0.05). Penetration depths and percentages increased from apically to coronally in all groups. The PUI and EDDY generally showed similar penetration depths and percentages to the CNI, except at the coronal root level (p > 0.05). In all groups, when PIPS was used, it showed greater penetration depth and percentage (p < 0.05). PIPS and SWEEPS techniques showed lowest and similar smear scores compared to PUI and EDDY in the apical area where access and effectiveness of the irrigation solution are difficult.Öğe Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists(2025) Bahadır, Hasibe Sevilay; Keskin, Neslihan Büşra; Kurşun Çakmak, Emine Şebnem; Güneç, Gürkan; Cesur Aydın, Kader; Peker, FatihObjectives: 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.
