rs-fMRI and machine learning for ASD diagnosis: A systematic review and meta-analysis

CP Santana, EA de Carvalho, ID Rodrigues… - Scientific reports, 2022 - nature.com
Abstract Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria
through a lengthy and time-consuming process. Much effort is being made to identify brain …

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

X Yang, N Zhang, P Schrader - Machine Learning with Applications, 2022 - Elsevier
This paper presents a comprehensive and practical review of autism spectrum disorder
(ASD) classification using several traditional machine learning and deep learning methods …

Effects of micro-sized and nano-sized WO3 on mass attenauation coefficients of concrete by using MCNPX code

HO Tekin, VP Singh, T Manici - Applied Radiation and Isotopes, 2017 - Elsevier
In the present work the effect of tungsten oxide (WO 3) nanoparticles on mass attenauation
coefficients of concrete has been investigated by using MCNPX (version 2.4. 0). The …

Identifying differences in brain activities and an accurate detection of autism spectrum disorder using resting state functional-magnetic resonance imaging: A spatial …

V Subbaraju, MB Suresh, S Sundaram… - Medical image …, 2017 - Elsevier
This paper presents a new approach for detecting major differences in brain activities
between Autism Spectrum Disorder (ASD) patients and neurotypical subjects using the …

[HTML][HTML] Autism spectrum disorder studies using fMRI data and machine learning: a review

M Liu, B Li, D Hu - Frontiers in Neuroscience, 2021 - frontiersin.org
Machine learning methods have been frequently applied in the field of cognitive
neuroscience in the last decade. A great deal of attention has been attracted to introduce …

YENİ MEDYA ESKİ MEDYAYA KARŞI: SAVAŞI KİM KAZANDI YA DA KİM KAZANACAK?

B Bulunmaz - Karadeniz Teknik Üniversitesi İletişim Araştırmaları …, 2014 - dergipark.org.tr
Teknolojinin tetiklediği yeni dünya düzeni, eski uygulamaları ve alışkanlıkları tamamen
değiştirmektedir. İnternetin yarattığı ve temel altyapısını oluşturduğu yeni medya ve internet …

Machine learning and rs-fMRI to identify potential brain regions associated with autism severity

ID Rodrigues, EA de Carvalho, CP Santana, GS Bastos - Algorithms, 2022 - mdpi.com
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized primarily
by social impairments that manifest in different severity levels. In recent years, many studies …

Deep manifold harmonic network with dual attention for brain disorder classification

X Sheng, J Chen, Y Liu, B Hu… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Numerous studies have shown that accurate analysis of neurological disorders contributes
to the early diagnosis of brain disorders and provides a window to diagnose psychiatric …

Learning common harmonic waves on Stiefel manifold–A new mathematical approach for brain network analyses

J Chen, G Han, H Cai, D Yang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Converging evidence shows that disease-relevant brain alterations do not appear in random
brain locations, instead, their spatial patterns follow large-scale brain networks. In this …

Case-control discrimination through effective brain connectivity

A Crimi, L Dodero, V Murino… - 2017 IEEE 14th …, 2017 - ieeexplore.ieee.org
Functional and structural connectivity convey different information about the brain. The
integration of these different approaches is receiving growing attention from the research …