Adolescent dysmorphic disorder model research based on machine learning

Leyao Bi

doi:10.1117/12.2691926

21 August 2023 Adolescent dysmorphic disorder model research based on machine learning

Leyao Bi

Proceedings Volume 12783, International Conference on Images, Signals, and Computing (ICISC 2023); 1278309 (2023) https://doi.org/10.1117/12.2691926
Event: International Conference on Images, Signals, and Computing (ICISC2023), 2023, Chengdu, China

Abstract

Nowadays, dysmorphic disorder among contemporary adolescents has attracted more and more attention from people of all social circles. The purpose of this study is to provide a useful self-evaluation model of adolescent image for assessing adolescents’ dysmorphic disorder situations. 249 teenagers participated in this study and various machine learning algorithms have been developed and utilized for building the self-evaluation model, such as the K-Nearest Neighbor algorithm, Naïve Bayes algorithm, and Principal Component Analysis algorithm. The best self-evaluation model developed in this project gave the highest accuracy of 76.92% on the testing set. For predicting the trend of dysmorphic disorder among contemporary Chinese adolescents, ordinary least squares linear regression model has been created, and then the percentages of different age stages to carry out major plastic surgery in 2022, 2023, and 2024 have been predicted

Citation Download Citation

Leyao Bi "Adolescent dysmorphic disorder model research based on machine learning", Proc. SPIE 12783, International Conference on Images, Signals, and Computing (ICISC 2023), 1278309 (21 August 2023); https://doi.org/10.1117/12.2691926

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