Background: In recent years, artificial intelligence (AI) and deep learning (DL) have made a considerable impact in dentistry, specifically in advancing image processing algorithms for detecting caries from radiographical images. Despite this progress, there is still a lack of data on the effectiveness of these algorithms in accurately identifying caries. This study provides an overview aimed at evaluating and comparing reviews that focus on the detection of using DL algorithms from 2D radiographs.
View Article and Find Full Text PDFObjective: Craniocervical junction morphology has been associated with Chiari malformation type I (CMI) symptom severity; however, little is known about its deterministic effect on surgical outcomes in patients across age and sex differences. The goal of the present study was to assess the effects of age and sex on surgical outcomes in CMI.
Methods: In the present study, the authors examined MRI-based morphometric data from 115 individuals diagnosed with CMI (54 adults including 39 women and 15 men, and 61 children including 24 girls and 37 boys) and correlated them with Chicago Chiari Outcome Scale (CCOS) scores obtained 1 year after posterior fossa decompression.
Clin Cosmet Investig Dent
October 2024
Purpose: The aim of this pilot study was to assess the knowledge and perceptions surrounding the use of fake snap-on veneers, as well as to evaluate the experiences of individuals who have used them.
Materials And Methods: This study was conducted between October 2021 and January 2022. A questionnaire was distributed through social media platforms to individuals aged >18 years in Saudi Arabia, which assessed their personal and sociodemographic information and perceptions and experiences with fake snap-on veneers.