A study of brain networks for autism spectrum disorder classification using resting-state functional connectivity-Reference-Cited by-同舟云学术

A study of brain networks for autism spectrum disorder classification using resting-state functional connectivity

Published:2022-06 Issue: Volume:8 Page:100290
ISSN:2666-8270
Container-title:Machine Learning with Applications
language:en
Short-container-title:Machine Learning with Applications

Author:

Yang Xin^ORCID,Zhang Ning^ORCID,Schrader Paul^ORCID

Publisher

Elsevier BV

Subject

General Medicine

Reference91 articles.

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

2. Machine learning based classification of resting-state fMRI features exemplified by metabolic state (hunger/satiety);Al-Zubaidi;Frontiers in Human Neuroscience,2019

3. Deep speech 2: End-to-end speech recognition in english and mandarin;Amodei,2016

4. Antidepressant effect on connectivity of the mood-regulating circuit: an FMRI study;Anand;Neuropsychopharmacology,2005

5. Classification of schizophrenia patients based on resting-state functional network connectivity;Arbabshirani;Frontiers in Neuroscience,2013

Cited by 29 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. Analyzing lower body movements using machine learning to classify autistic children;Biomedical Signal Processing and Control;2024-08

2. A Deep Neural Network Approach for Autism Spectrum Disorder Detection Using Multiple Brain Atlases with Resting-State Functional Magnetic Resonance Imaging Data;2024 IEEE Students Conference on Engineering and Systems (SCES);2024-06-21

3. Impact of Machine Learning and Deep Learning Techniques in Autism;Advances in Medical Technologies and Clinical Practice;2024-05-31

4. Classification of Autism Spectrum Disorder from rs-fMRI Scans by Feature Reduction and Ensemble Machine Learning Classifier;2024 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE);2024-04-25

5. Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods;Neural Computing and Applications;2024-04-22