Machine Learning Algorithms for the Diagnosis of Class III Malocclusions in Children.

Ling ZhaoXiaozhi ChenJuneng HuangShuixue MoMin GuNa KangShaohua SongXuejun ZhangBohui LiangMin Tang

Published in: Children (Basel, Switzerland) (2024)

Our findings suggest that ML models based on cephalometric data could effectively assist dentists to classify dental, functional and skeletal Class III malocclusions in children. In addition, features such as SN_GoMe, U1_NA and Overjet can as important indicators for predicting the severity of Class III malocclusions.

Keyphrases

machine learning
young adults
big data
artificial intelligence
deep learning
electronic health record
oral health
data analysis