Automated skeletal classification using lateral cephalogram based on AI in Journal of Dental Research

This study aims to provide an accurate and robust skeletal diagnostic system by incorporating a convolutional neural network (CNN) into a one-step, end-to-end diagnostic system using lateral cephalograms. A multimodal CNN model was constructed based on 5,890 lateral cephalograms and demographic data as an input. The proposed system exhibited greater than 90% sensitivity, specificity, and accuracy for vertical and sagittal skeletal diagnosis. The proposed CNN incorporated system showed potential for skeletal orthodontic diagnosis without the need for intermediary landmarking procedures.