Kiyomi Kohinata, Tomoya Kitano, Wataru Nishiyama, Mizuho Mori, Yukihiro Iida, Hiroshi Fujita, Akitoshi Katsumata
OBJECTIVE: This study explored the feasibility of using deep learning for profiling of panoramic radiographs. STUDY DESIGN: Panoramic radiographs of 1000 patients were used. Patients were categorized using seven dental or physical characteristics: age, gender, mixed or permanent dentition, number of presenting teeth, impacted wisdom tooth status, implant status, and prosthetic treatment status. A Neural Network Console (Sony Network Communications Inc., Tokyo, Japan) deep learning system and the VGG-Net deep convolutional neural network were used for classification...
April 2023: Oral Radiology