Classification of ADHD with fMRI data and multi-objective optimization-Reference-Cited by-同舟云学术

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Classification of ADHD with fMRI data and multi-objective optimization

Published:2020-11 Issue: Volume:196 Page:105676
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Shao Lizhen,You Yang,Du Haipeng,Fu Dongmei

Funder

Scientific and Technological Innovation Foundation

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference40 articles.

1. Diagnostic and Statistical Manual of Mental Disorders: DSM- 5,2013

2. Annual research review: a meta-analysis of the worldwide prevalence of mental disorders in children and adolescents;Polanczyk;J. Child Psychol. Psychiatry,2015

3. Attributed graph distance measure for automatic detection of attention deficit hyperactive disordered subjects;Dey;Front. Neural Circuits,2014

4. Is the Theta/Beta EEG marker for ADHD inherently flawed?;Saad;J. Attent. Disord.,2015

5. Classification of ADHD and non-ADHD subjects using a universal background model;Marcano;Biomed. Signal Process. Control,2018

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2. An Improved Model for The Diagnosis of Attention Deficit/Hyperactivity Disorder (ADHD) Using Resting-state fMRI Data;2024 International Conference on Machine Intelligence and Smart Innovation (ICMISI);2024-05-12

3. iPAL: A Machine Learning Based Smart Healthcare Framework for Automatic Diagnosis of Attention Deficit/Hyperactivity Disorder;SN Computer Science;2024-04-13

4. A review of ADHD detection studies with machine learning methods using rsfMRI data;NMR in Biomedicine;2024-03-12

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