Deep learning-based diagnosis of Alzheimer's disease
Alzheimer's disease (AD), the most familiar type of dementia, is a severe concern in modern
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
[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 …
Analysis of features of Alzheimer's disease: Detection of early stage from functional brain changes in magnetic resonance images using a finetuned ResNet18 network
One of the first signs of Alzheimer's disease (AD) is mild cognitive impairment (MCI), in
which there are small variants of brain changes among the intermediate stages. Although …
which there are small variants of brain changes among the intermediate stages. Although …
AlzheimerNet: An effective deep learning based proposition for alzheimer's disease stages classification from functional brain changes in magnetic resonance images
Alzheimer's disease is largely the underlying cause of dementia due to its progressive
neurodegenerative nature among the elderly. The disease can be divided into five stages …
neurodegenerative nature among the elderly. The disease can be divided into five stages …
fMRI-Based Alzheimer's Disease Detection Using the SAS Method with Multi-Layer Perceptron Network
A Chelladurai, DL Narayan, PB Divakarachari… - Brain Sciences, 2023 - mdpi.com
In the present scenario, Alzheimer's Disease (AD) is one of the incurable neuro-
degenerative disorders, which accounts for nearly 60% to 70% of dementia cases. Currently …
degenerative disorders, which accounts for nearly 60% to 70% of dementia cases. Currently …
Neuroimaging modalities in Alzheimer's disease: diagnosis and clinical features
Alzheimer's disease (AD) is a neurodegenerative disease causing progressive cognitive
decline until eventual death. AD affects millions of individuals worldwide in the absence of …
decline until eventual death. AD affects millions of individuals worldwide in the absence of …
An evolutionary explainable deep learning approach for Alzheimer's MRI classification
Abstract Deep Neural Networks (DNN) are prominent Machine Learning (ML) algorithms
widely used, especially in medical tasks. Among them, Convolutional Neural Networks …
widely used, especially in medical tasks. Among them, Convolutional Neural Networks …
Structural MRI texture analysis for detecting Alzheimer's disease
Purpose: Alzheimer's disease (AD) has the highest worldwide prevalence of all
neurodegenerative disorders, no cure, and low ratios of diagnosis accuracy at its early stage …
neurodegenerative disorders, no cure, and low ratios of diagnosis accuracy at its early stage …
Comparison of different convolutional neural network activation functions and methods for building ensembles for small to midsize medical data sets
CNNs and other deep learners are now state-of-the-art in medical imaging research.
However, the small sample size of many medical data sets dampens performance and …
However, the small sample size of many medical data sets dampens performance and …
A review of methods of diagnosis and complexity analysis of Alzheimer's disease using EEG signals
M Ouchani, S Gharibzadeh… - BioMed Research …, 2021 - Wiley Online Library
This study will concentrate on recent research on EEG signals for Alzheimer's diagnosis,
identifying and comparing key steps of EEG‐based Alzheimer's disease (AD) detection …
identifying and comparing key steps of EEG‐based Alzheimer's disease (AD) detection …