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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 …
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
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 …
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
Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive
abilities. Recently, various neuroimaging modalities and machine learning methods have …
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
Heterogeneous mental disorders such as Autism Spectrum Disorder (ASD) are notoriously
difficult to diagnose, especially in children. The current psychiatric diagnostic process is …
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
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 …
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
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 …
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 …
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
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 …
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 …
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
Mild cognitive impairment (MCI), a condition characterizing poor cognition, is associated
with aging and depicts early symptoms of severe cognitive impairment, known as …
with aging and depicts early symptoms of severe cognitive impairment, known as …