Orthodontic Treatment Planning based on Artificial Neural Networks.

ABSTRACT: In this study, multilayer perceptron artificial neural networks are used to predict orthodontic treatment plans, including the determination of extraction-nonextraction, extraction patterns, and anchorage patterns. The neural network can output the feasibilities of several applicable treatment plans, offering orthodontists flexibility in making decisions. The neural network models show an accuracy of 94.0% for extraction-nonextraction prediction, with an area under the curve (AUC) of 0.982, a sensitivity of 94.6%, and a specificity of 93.8%. The accuracies of the extraction patterns and anchorage patterns are 84.2% and 92.8%, respectively. The most important features for prediction of the neural networks are "crowding, upper arch" "ANB" and "curve of Spee". For handling discrete input feat

SUBMITTER: Li P 

PROVIDER: S-EPMC6375961 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature