Artificial intelligence-based automated preprocessing and classification of impacted maxillary canines in panoramic radiographs.

OBJECTIVES: Automating the digital workflow for diagnosing impacted canines using panoramic radiographs (PRs) is challenging. This study explored feature extraction, automated cropping, and classification of impacted and nonimpacted canines as a first step. METHODS: A convolutional neural network with SqueezeNet architecture was first trained to classify two groups of PRs (91with and 91without impacted canines) on the MATLAB programming platform. Based on results, the need to crop the PRs was realized. Next, artificial intelligence (AI) detectors were trained to identify specific landmarks (maxillary central incisors, lateral incisors, canines, bicuspids, nasal area, and the mandibular ramus) on the PRs. Landmarks were then explored to guide cropping of the PRs. Finally, improvements in classification of automatically cropped PRs were studied. RESULTS: Without cropping, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for classifying impacted and nonimpacted canine was 84%. Landmark training showed that detectors could correctly identify upper central incisors and the ramus in ∼98% of PRs. The combined use of the mandibular ramus and maxillary central incisors as guides for cropping yielded the best results (∼10% incorrect cropping). When automatically cropped PRs were used, the AUC-ROC improved to 96%. CONCLUSIONS: AI algorithms can be automated to preprocess PRs and improve the identification of impacted canines.

Prevalence of Dental Caries in Children Visiting a Dental College and Hospital in the United Arab Emirates: A Cross-sectional Study.

AIM: The purpose of this study was to examine the prevalence of dental caries in school children visiting a dental college and hospital and investigate the associated risk factors. MATERIALS AND METHODS: Eighty children were recruited in this study between the ages of 6-12 years. The caries prevalence of decayed, missing, filled teeth (DMFT) was recorded using an evaluation form. A structured questionnaire was used to understand the associated risk factors. RESULTS: The caries prevalence in the population was found to be at 91.25%. There was a strong negative correlation between age and dental caries and the results were statistically significant with p-value being less than 0.0001. The duration of bottle and breastfeeding, frequency of teeth brushing, adult supervision during brushing, consumption frequency of sweets, and the frequency or timing of children's dental visits were found to be positively associated with dental caries and these results were statistically significant with p-value being less than 0.05. CONCLUSION: A high prevalence of dental caries was observed among the population visiting the dental college and hospital. Encouraging dental health education, including promoting the significance of good oral hygiene practices, is crucial. CLINICAL SIGNIFICANCE: The study emphasizes the rising prevalence of dental caries and underscores the need for dental health education and the promotion of good oral hygiene practices to prevent complications and reduce their prevalence.