Detection of Attention Deficit Hyperactivity Disorder using Decision-level Fusion of Brain Connectivity Information Based on Deep Learning-Reference-Cited by-同舟云学术

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Detection of Attention Deficit Hyperactivity Disorder using Decision-level Fusion of Brain Connectivity Information Based on Deep Learning

Published:2023-11-10 Issue: Volume: Page:
ISSN:
Container-title:2023 Medical Technologies Congress (TIPTEKNO)
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Author:

Cura Ozlem Karabiber¹,Ciklacandir Fatma Gunseli²,Akan Aydin³,Atli Sibel Kocaaslan⁴

Affiliation:

1. Izmir Katip Celebi University,Dept. of Biomedical Engineering,Izmir,TURKEY

2. Izmir Katip Celebi University,Dept. of Computer Engineering,Izmir,TURKEY

3. Izmir University of Economics,Dept. of Electrical and Electronics Eng.,Izmir,TURKEY

4. Izmir Katip Celebi University,Faculty of Medicine,Dept. of Biophysics,Izmir,TURKEY

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10359115/10359172/10359178.pdf?arnumber=10359178

Reference19 articles.

1. New interdependence feature of EEG signals as a biomarker of timing deficits evaluated in Attention-Deficit/Hyperactivity Disorder detection

2. ADHD detection using dynamic connectivity patterns of EEG data and ConvLSTM with attention framework

3. Detecting Attention Levels in ADHD Children with a Video Game and the Measurement of Brain Activity with a Single-Channel BCI Headset

4. Diagnosis of Attention Deficit Hyperactivity Disorder with combined time and frequency features

5. Performance analysis of univariate and multivariate EEG measurements in the diagnosis of ADHD

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