Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer's disease, Parkinson's …
MBT Noor, NZ Zenia, M Gabriela, G Cicerchi, H Colin… - … : Journal International of …, 2022 - search.ebscohost.com
This article examines the role of parents in hel** teachers in mastering Arabic vocabulary
for elementery school students. In addition, this article aims to make parents aware of their …
for elementery school students. In addition, this article aims to make parents aware of their …
[HTML][HTML] A comprehensive survey on the detection, classification, and challenges of neurological disorders
Simple Summary This study represents a resourceful review article that can deliver
resources on neurological diseases and their implemented classification algorithms to …
resources on neurological diseases and their implemented classification algorithms to …
[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 …
Deep-learning-based diagnosis and prognosis of Alzheimer's disease: a comprehensive review
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most
common cause of Dementia. Neuroimaging analyses, such as T1 weighted magnetic …
common cause of Dementia. Neuroimaging analyses, such as T1 weighted magnetic …
[Retracted] Classification of Alzheimer's Disease Using Gaussian‐Based Bayesian Parameter Optimization for Deep Convolutional LSTM Network
Alzheimer's disease (AD) is one of the most important causes of mortality in elderly people,
and it is often challenging to use traditional manual procedures when diagnosing a disease …
and it is often challenging to use traditional manual procedures when diagnosing a disease …
[Retracted] An Exploration: Alzheimer's Disease Classification Based on Convolutional Neural Network
Alzheimer's disease (AD) is the most generally known neurodegenerative disorder, leading
to a steady deterioration in cognitive ability. Deep learning models have shown outstanding …
to a steady deterioration in cognitive ability. Deep learning models have shown outstanding …
Structural biomarker‐based Alzheimer's disease detection via ensemble learning techniques
Alzheimer's disease (AD) is a degenerative neurological disorder with incurable
characteristics. To identify the substantial solution, we used a structural biomarker (structural …
characteristics. To identify the substantial solution, we used a structural biomarker (structural …
[HTML][HTML] Research on early diagnosis of Alzheimer's disease based on dual fusion cluster graph convolutional network
L Meng, Q Zhang - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract Objective Mild Cognitive Impairment (MCI) is an early stage of Alzheimer's Disease
(AD), often mistaken for natural aging. Early detection and treatment of MCI are crucial for …
(AD), often mistaken for natural aging. Early detection and treatment of MCI are crucial for …