Our work in oral medicine and radiology

Using deep learning to segment impacted molar teeth from panoramic radiographs

This study evaluated the effectiveness of hybrid deep learning and vision models in classifying and segmenting impacted molar teeth from full-mouth panoramic radiographs.

Estimating Age and Sex from Dental Panoramic Radiographs Using Neural Networks and Vision–Language Models

he purpose of this study was to compare multiple deep learning models for estimating age and sex using dental panoramic radiographs and identify the most successful deep learning models for the specified tasks

Predicting Leukoplakia and Oral Squamous Cell Carcinoma Using Machine Learning

to assess the effectiveness of the best performing interpretable machine learning models in the diagnoses of leukoplakia and oral squamous cell carcinoma

Using AI for age and biological gender estimation from dental radiographs

This study aimed to estimate human age and gender from panoramic radiographs using various deep learning techniques
while using explainability to have a novel hybrid unsupervised model explain the decision-making process.

Computer vision methods to track endodontic treatment status after correcting noise in dental radiographs

The study aimed to evaluate the effects of denoising and data balancing on deep learning to detect endodontic treatment outcomes from radiographs.