[HTML][HTML] Application of artificial intelligence in the MRI classification task of human brain neurological and psychiatric diseases: a scoping review
Z Zhang, G Li, Y Xu, X Tang - Diagnostics, 2021 - mdpi.com
Artificial intelligence (AI) for medical imaging is a technology with great potential. An in-
depth understanding of the principles and applications of magnetic resonance imaging …
depth understanding of the principles and applications of magnetic resonance imaging …
Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization
Background The recent deep learning-based studies on the classification of schizophrenia
(SCZ) using MRI data rely on manual extraction of feature vector, which destroys the 3D …
(SCZ) using MRI data rely on manual extraction of feature vector, which destroys the 3D …
[HTML][HTML] A brief review of artificial intelligence applications and algorithms for psychiatric disorders
GD Liu, YC Li, W Zhang, L Zhang - Engineering, 2020 - Elsevier
A number of brain research projects have recently been carried out to study the etiology and
mechanisms of psychiatric disorders. Although psychiatric disorders are part of the brain …
mechanisms of psychiatric disorders. Although psychiatric disorders are part of the brain …
[HTML][HTML] Alzheimer's disease diagnosis from diffusion tensor images using convolutional neural networks
Machine learning algorithms are currently being implemented in an escalating manner to
classify and/or predict the onset of some neurodegenerative diseases; including Alzheimer's …
classify and/or predict the onset of some neurodegenerative diseases; including Alzheimer's …
3-D CNN-based multichannel contrastive learning for Alzheimer's disease automatic diagnosis
J Li, Y Wei, C Wang, Q Hu, Y Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a common progressive neurodegenerative disease in the
elderly. Mild cognitive impairment (MCI) is the symptomatic predementia stage of AD …
elderly. Mild cognitive impairment (MCI) is the symptomatic predementia stage of AD …
Decoding and mapping task states of the human brain via deep learning
Support vector machine (SVM)‐based multivariate pattern analysis (MVPA) has delivered
promising performance in decoding specific task states based on functional magnetic …
promising performance in decoding specific task states based on functional magnetic …
[HTML][HTML] Automated medical diagnosis of Alzheimer´ s disease using an efficient net convolutional neural network
Alzheimer's disease (AD) poses an enormous challenge to modern healthcare. Since 2017,
researchers have been using deep learning (DL) models for the early detection of AD using …
researchers have been using deep learning (DL) models for the early detection of AD using …
[HTML][HTML] AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction
Abstract The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk
converting to Alzheimer's Disease (AD) is critical for effective intervention and patient …
converting to Alzheimer's Disease (AD) is critical for effective intervention and patient …
3d Convolutional neural networks for diagnosis of alzheimer's disease via structural mri
Alzheimer's Disease (AD) is a widespread neurodegenerative disease caused by structural
changes in the brain and leads to deterioration of cognitive functions. Patients usually …
changes in the brain and leads to deterioration of cognitive functions. Patients usually …
Machine learning for predicting cognitive diseases: methods, data sources and risk factors
Abstract Machine learning and data mining approaches are being successfully applied to
different fields of life sciences for the past 20 years. Medicine is one of the most suitable …
different fields of life sciences for the past 20 years. Medicine is one of the most suitable …