Severity Assessment of Social Anxiety Disorder Using Deep Learning Models on Brain Effective Connectivity-Reference-Cited by-同舟云学术

Severity Assessment of Social Anxiety Disorder Using Deep Learning Models on Brain Effective Connectivity

Published:2021 Issue: Volume:9 Page:86899-86913
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Al-Ezzi Abdulhakim^ORCID,Yahya Norashikin^ORCID,Kamel Nidal^ORCID,Faye Ibrahima^ORCID,Alsaih Khaled^ORCID,Gunaseli Esther

Funder

Ministry of Higher Education Malaysia under Higher Institutional Centre of Excellence (HICoE) Scheme awarded to Centre for Intelligent Signal and Imaging Research

Yayasan Universiti Teknologi PETRONAS

Medical Research Ethics Committee of the Royal College of Medicine Perak, Kuala Lumpur University, under Approval

Helsinki Declaration

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09454451.pdf?arnumber=9454451

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Anxiety brain topographic maps and its classification using quantitative electroencephalography;Intelligent Computing Techniques in Biomedical Imaging;2025

2. Social anxiety prediction based on ERP features: A deep learning approach;Journal of Affective Disorders;2024-12

3. TAGformer: A Multimodal Physiological Signals Fusion Network for Pilot Stress Recognition;IEEE Sensors Journal;2024-07-01

4. Integrating EEG and Ensemble Learning for Accurate Grading and Quantification of Generalized Anxiety Disorder: A Novel Diagnostic Approach;Diagnostics;2024-05-28

5. Enhancing Anxiety Diagnosis through ADABOOST-Assisted Decision-Level Fusion;2024-05-10