Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures

Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures

IntroductionThe early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression and development of SAD. This paper proposes an effective method to classify the...

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Bibliographic Details
Main Authors: Abdulhakim Al-Ezzi, Nidal Kamel, Amal A. Al-Shargabi, Fares Al-Shargie, Alaa Al-Shargabi, Norashikin Yahya, Mohammed Isam Al-Hiyali
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Psychiatry
Subjects:
EEG
graph theory analysis
social anxiety disorders
machine learning
effective connectivity
partial directed coherence
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1155812/full

Internet

https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1155812/full

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