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Incidence of Orthodontic Problems in Northern Cypriot Population

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Aim: Technologies related to big data are progressively used for various research purposes in the fields of dentistry and health-care informatics. Large amounts of clinical data have been achieved and acquired at an exceptional acceleration and advancement. The actively developing field of big data analysis has started to play a critical and decisive role in the progression of dental practices and research. It has implemented tools to collect, regulate, interpret, and comprehend enormous volumes of distinct, structured, and unstructured data established from the present healthcare systems. Big data analysis has been lately devoted in the direction of encouraging and assisting the process of problem detection and care delivery. Our study aimed at measuring the frequentness of orthodontic problems, incidence of malocclusion and the orthodontic treatment demand among children who attend secondary schools in Northern Cyprus. Methods: For the present survey, our sample included 426 school children (203 females and 223 males) who are 12–15 years of age. Molar relation in each child was assessed according to Angle's classification. To evaluate the need and demand for orthodontic treatment, the ICON index was then used. Occlusal features such as overbite and overjet were measured and the presence of malocclusal characteristics such as cross bite, deep bite or open bite was examined and recorded for each subject. Our findings indicated that among this Northern Cypriot school population: (20.6%) had no occurrence of malocclusion, (74.6%) were found to have a Class I molar relation, (21.1%) had a Class II molar relation (Division 1, 13.6%; Division 2, 1.6%) and (3.3%) had a Class III malocclusion. Moreover, (20.2%) of all the examined children were found in need of orthodontic treatment. Digital modelling derived from CBCT scanning of plaster casts is a reliable method to assure the accuracy of measurements obtained directly from clinical and dental examination. Results: 74.6% of all subjects were found to have class I dental malocclusion; class II division 1 were calculated at 13,6%, class II division 2 were 1,6%, class II subdivision 4,2%, class III were calculated to be at 3,3% and class III subdivision 2,5%. Conclusion: The most common orthodontic malocclusion in Northern Cypriot school children is Class I and the least common one is Class II division 2.

Keywords: CBCT; DATA-DRIVEN APPLICATION; DIGITAL MODELS; EPIDEMIOLOGY; HEALTHCARE; IMAGING TECHNIQUES; PERMANENT DENTITION

Document Type: Research Article

Publication date: 01 January 2021

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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