Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network-Reference-Cited by-同舟云学术

Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network

Published:2020-01-14 Issue: Volume:13 Page:
ISSN:1662-453X
Container-title:Frontiers in Neuroscience
language:
Short-container-title:Front. Neurosci.

Author:

Sherkatghanad Zeinab,Akhondzadeh Mohammadsadegh,Salari Soorena,Zomorodi-Moghadam Mariam,Abdar Moloud,Acharya U. Rajendra,Khosrowabadi Reza,Salari Vahid

Publisher

Frontiers Media SA

Subject

General Neuroscience

Reference45 articles.

1. Deriving reproducible biomarkers from multi-site resting-state data: an autism-based example;Abraham;NeuroImage,2017

2. Combination of rs-fMRI and sMRI data to discriminate autism spectrum disorders in young children using deep belief network;Aghdam;J. Digit. Imaging,2018

3. Functional connectivity magnetic resonance imaging classification of autism;Anderson;Brain,2011

4. Bootstrapping graph convolutional neural networks for autism spectrum disorder classification;Anirudh;arXiv:1704.07487 [stat.ML].,2017

Cited by 132 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. An evaluation of machine learning approaches for early diagnosis of autism spectrum disorder;Healthcare Analytics;2024-06

2. Novel deep learning models with novel integrated activation functions for autism screening: AutiNet and MinAutiNet;Expert Systems with Applications;2024-03

3. Multimodal Deep Learning in Early Autism Detection—Recent Advances and Challenges;RAiSE-2023;2024-01-23

4. Deep learning with image-based autism spectrum disorder analysis: A systematic review;Engineering Applications of Artificial Intelligence;2024-01

5. Classification of Autism Spectrum Disorder Using a 3D-CNN Ensemble Model and Regional Homogeneity Data from the ABIDE I Dataset;IFMBE Proceedings;2024