Publications by authors named "E S A Alhaija"

Background: The collum angle, tooth dimensions, root length, and alveolar bone thickness have a significant impact on orthodontic diagnosis and treatment planning. The boundaries of orthodontic tooth movement are determined by alveolar bone thickness and dimensions while the collum angle determines the appropriate positioning of the root relative to the cortical plate. This study aimed to compare the collum angle, crown dimensions, root length, and alveolar bone thickness of the upper and lower incisors, canines, and premolars in subjects with varying anteroposterior relationships.

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Objectives: To detect any association between palatally displaced canine (PDC) and nasal septal deviation (NSD), palatal bone thickness and volume, and nasal airway dimensions and volume.

Materials And Methods: A total of 92 patients were included and subdivided into two groups: group 1, unilateral PDCs (44 patients), and group 2, normally erupted canines (NDCs) (48 subjects). The following variables were measured using cone-beam computed tomography: presence and type of NSD, nasal width, inferior conchae, hard palate and nasal septum thickness, maxillary bone and nasal airway volumes.

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Introduction: Mouthguards (MGs) have the potential to prevent contact sport-related dental injuries. However, varying perceptions of their effectiveness persist, influencing recommendations by dental professionals.

Aim: To assess the attitudes, knowledge, and perceptions of orthodontists, other dental practitioners (general dentists and other dental specialists), and orthodontic patients involved in contact sports regarding the use of MGs.

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Objectives: This review aimed to map taxonomy frameworks, descriptions, and applications of immersive technologies in the dental literature.

Data: The Preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) guidelines was followed, and the protocol was registered at open science framework platform (https://doi.org/10.

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The objective of this study is to use a deep-learning model based on CNN architecture to detect the second mesiobuccal (MB2) canals, which are seen as a variation in maxillary molars root canals. In the current study, 922 axial sections from 153 patients' cone beam computed tomography (CBCT) images were used. The segmentation method was employed to identify the MB2 canals in maxillary molars that had not previously had endodontic treatment.

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