Cargando…
MRI-Based Radiomic Machine-Learning Model May Accurately Distinguish between Subjects with Internet Gaming Disorder and Healthy Controls
Purpose To identify cerebral radiomic features related to the diagnosis of Internet gaming disorder (IGD) and construct a radiomics-based machine-learning model for IGD diagnosis. Methods A total of 59 treatment-naïve subjects with IGD and 69 age- and sex-matched healthy controls (HCs) were recruite...
Autores principales: | Han, Xu, Wei, Lei, Sun, Yawen, Hu, Ying, Wang, Yao, Ding, Weina, Wang, Zhe, Jiang, Wenqing, Wang, He, Zhou, Yan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774247/ https://www.ncbi.nlm.nih.gov/pubmed/35053787 http://dx.doi.org/10.3390/brainsci12010044 |
Ejemplares similares
-
Alterations of Resting-State Static and Dynamic Functional Connectivity of the Dorsolateral Prefrontal Cortex in Subjects with Internet Gaming Disorder
por: Han, Xu, et al.
Publicado: (2018) -
Interaction Between Smoking and Internet Gaming Disorder on Spontaneous Brain Activity
por: Qiu, Xianxin, et al.
Publicado: (2020) -
Resting-State Activity of Prefrontal-Striatal Circuits in Internet Gaming Disorder: Changes With Cognitive Behavior Therapy and Predictors of Treatment Response
por: Han, Xu, et al.
Publicado: (2018) -
Different Resting-State Functional Connectivity Alterations in Smokers and Nonsmokers with Internet Gaming Addiction
por: Chen, Xue, et al.
Publicado: (2014) -
Radiomic features from MRI distinguish myxomas from myxofibrosarcomas
por: Martin-Carreras, Teresa, et al.
Publicado: (2019)