Resting-state functional MRI: everything that nonexperts have always wanted to know

H Lv, Z Wang, E Tong, LM Williams… - American Journal of …, 2018 - ajnr.org
Resting-state fMRI was first described by Biswal et al in 1995 and has since then been
widely used in both healthy subjects and patients with various neurologic, neurosurgical …

Diagnostic power of resting‐state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review

B Ibrahim, S Suppiah, N Ibrahim… - Human brain …, 2021 - Wiley Online Library
Resting‐state fMRI (rs‐fMRI) detects functional connectivity (FC) abnormalities that occur in
the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC …

Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning

A Alorf, MUG Khan - Computers in Biology and Medicine, 2022 - Elsevier
Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive
abilities. Recently, various neuroimaging modalities and machine learning methods have …

ASD-DiagNet: a hybrid learning approach for detection of autism spectrum disorder using fMRI data

T Eslami, V Mirjalili, A Fong, AR Laird… - Frontiers in …, 2019 - frontiersin.org
Heterogeneous mental disorders such as Autism Spectrum Disorder (ASD) are notoriously
difficult to diagnose, especially in children. The current psychiatric diagnostic process is …

[HTML][HTML] Applications of artificial intelligence to aid early detection of dementia: a sco** review on current capabilities and future directions

R Li, X Wang, K Lawler, S Garg, Q Bai, J Alty - Journal of biomedical …, 2022 - Elsevier
Abstract Background & Objective With populations aging, the number of people with
dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases …

Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM

SH Hojjati, A Ebrahimzadeh, A Khazaee… - Journal of neuroscience …, 2017 - Elsevier
Background We investigated identifying patients with mild cognitive impairment (MCI) who
progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do …

Graph theory and brain connectivity in Alzheimer's disease

J DelEtoile, H Adeli - The Neuroscientist, 2017 - journals.sagepub.com
This article presents a review of recent advances in neuroscience research in the specific
area of brain connectivity as a potential biomarker of Alzheimer's disease with a focus on the …

Predicting conversion from MCI to AD by integrating rs-fMRI and structural MRI

SH Hojjati, A Ebrahimzadeh, A Khazaee… - Computers in biology …, 2018 - Elsevier
Structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) have provided promising
results in the diagnosis of Alzheimer's disease (AD), though the utility of integrating sMRI …

Brain MRI analysis using a deep learning based evolutionary approach

H Shahamat, MS Abadeh - Neural Networks, 2020 - Elsevier
Convolutional neural network (CNN) models have recently demonstrated impressive
performance in medical image analysis. However, there is no clear understanding of why …

Evaluation of neural degeneration biomarkers in the prefrontal cortex for early identification of patients with mild cognitive impairment: an fNIRS study

D Yang, KS Hong, SH Yoo, CS Kim - Frontiers in human neuroscience, 2019 - frontiersin.org
Mild cognitive impairment (MCI), a condition characterizing poor cognition, is associated
with aging and depicts early symptoms of severe cognitive impairment, known as …