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    Evaluation of a Decision Support System Developed with Deep Learning Approach for Detecting Dental Caries with Cone-Beam Computed Tomography Imaging
    (Mdpi, 2023) Amasya, Hakan; Alkhader, Mustafa; Serindere, Goezde; Futyma-Gabka, Karolina; Aktuna Belgin, Ceren; Gusarev, Maxim; Ezhov, Matvey
    This study aims to investigate the effect of using an artificial intelligence (AI) system (Diagnocat, Inc., San Francisco, CA, USA) for caries detection by comparing cone-beam computed tomography (CBCT) evaluation results with and without the software. 500 CBCT volumes are scored by three dentomaxillofacial radiologists for the presence of caries separately on a five-point confidence scale without and with the aid of the AI system. After visual evaluation, the deep convolutional neural network (CNN) model generated a radiological report and observers scored again using AI interface. The ground truth was determined by a hybrid approach. Intra- and inter-observer agreements are evaluated with sensitivity, specificity, accuracy, and kappa statistics. A total of 6008 surfaces are determined as 'presence of caries' and 13,928 surfaces are determined as 'absence of caries' for ground truth. The area under the ROC curve of observer 1, 2, and 3 are found to be 0.855/0.920, 0.863/0.917, and 0.747/0.903, respectively (unaided/aided). Fleiss Kappa coefficients are changed from 0.325 to 0.468, and the best accuracy (0.939) is achieved with the aided results. The radiographic evaluations performed with aid of the AI system are found to be more compatible and accurate than unaided evaluations in the detection of dental caries with CBCT images.
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    Evaluation of knowledge and awareness about teledentistry among dentists and patients living in Turkey
    (Wroclaw Medical Univ, 2023) Oezveren, Neslihan; Sevinc, Buesra; Guengoer, Ayca Sarialioglu; Baltaci, Ezgi; Serindere, Goezde; Oezguer, Oezge
    Background. Teledentistry is a field of telemedicine that combines digital technology and clinical dentistry, enabling remote communication between dentists and patients. Objectives. The aim of the present study was to evaluate the knowledge and awareness of dentists and patients about teledentistry in Turkey.Material and methods. This cross-sectional study was conducted among general and specialist dentists in Turkey, and dental patients in Edirne, Turkey. A questionnaire prepared in Google Docs was shared virtually among Turkish dentists, as well as administered to the patients referred to the university dental clinic in Edirne.Results. Among the 336 dentists participating in the study, 69.9% were female, 39.6% were working in the profession for 1-5 years, and 48.5% were specialist dentists. A total of 86.9% of dentists stated they would like to use teledentistry for radiological examinations, some follow-up examinations, and for follow-up during holidays. There were 21.1% of dentists who thought that teledentistry practices could be the new standard of oral healthcare, and only 34.0% were willing to try such practices. Among the 447 patients in the study, 49.9% were female, 79.0% were aged 20-44 years, and 54.4% had middle income. There were 74.5% of patients who stated that it would be easier to communicate with the dentist via a teledentistry application, 80.3% of patients in the underserved regions stated it would facilitate access to the dentist, 76.3% of patients stated that it would reduce costs, and 88.8% of patients thought that this method could help overcome the problem of isolation during the coronavirus disease 2019 (COVID-2019) pandemic period.Conclusions. Based on the results, it can be said that the teledentistry approach would provide con-venience for both dentists and patients in terms of dentist-patient communication, cost and efficiency of dental care.