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 …
An intelligent system for early recognition of Alzheimer's disease using neuroimaging
Alzheimer's disease (AD) is a neurodegenerative disease that affects brain cells, and mild
cognitive impairment (MCI) has been defined as the early phase that describes the onset of …
cognitive impairment (MCI) has been defined as the early phase that describes the onset of …
Pixel-level fusion approach with vision transformer for early detection of Alzheimer's disease
Alzheimer's disease (AD) has become a serious hazard to human health in recent years,
and proper screening and diagnosis of AD remain a challenge. Multimodal neuroimaging …
and proper screening and diagnosis of AD remain a challenge. Multimodal neuroimaging …
Improved CNN based on batch normalization and adam optimizer
After evaluating the difficulty of CNNs in extracting convolution features, this paper
suggested an improved convolutional neural network (CNN) method (ICNN-BNDOA), which …
suggested an improved convolutional neural network (CNN) method (ICNN-BNDOA), which …
A novel CNN architecture for accurate early detection and classification of Alzheimer's disease using MRI data
Alzheimer's disease (AD) is a debilitating neurodegenerative disorder that requires accurate
diagnosis for effective management and treatment. In this article, we propose an architecture …
diagnosis for effective management and treatment. In this article, we propose an architecture …
[HTML][HTML] Multi input–Multi output 3D CNN for dementia severity assessment with incomplete multimodal data
Alzheimer's Disease is the most common cause of dementia, whose progression spans in
different stages, from very mild cognitive impairment to mild and severe conditions. In clinical …
different stages, from very mild cognitive impairment to mild and severe conditions. In clinical …
[HTML][HTML] An Alzheimer's disease classification model using transfer learning Densenet with embedded healthcare decision support system
AW Saleh, G Gupta, SB Khan, NA Alkhaldi… - Decision Analytics …, 2023 - Elsevier
Abstract Training a Convolutional Neural Network (CNN) from scratch is time-consuming
and expensive. In this study, we propose implementing the DenseNet architecture for …
and expensive. In this study, we propose implementing the DenseNet architecture for …
Demystifying evidential Dempster Shafer-based CNN architecture for fetal plane detection from 2D ultrasound images leveraging fuzzy-contrast enhancement and …
Ultrasound imaging is a valuable tool for assessing the development of the fetal during
pregnancy. However, interpreting ultrasound images manually can be time-consuming and …
pregnancy. However, interpreting ultrasound images manually can be time-consuming and …
Heart disease classification using machine learning models
Heart Disease (HD) is a candidate for the utmost communal death-recording diseases in
history and an early detection is a herculean task for countless physicians. This paper aims …
history and an early detection is a herculean task for countless physicians. This paper aims …
Enhanced Alzheimer's disease classification using multilayer deep convolutional neural network-based experimentations
SA Kumar, S Sasikala - Iranian Journal of Science and Technology …, 2023 - Springer
Alzheimer's disease (AD) is an advanced neurological disorder and the main cause of
dementia in the elderly. Early detection of AD is critical for preventing brain damage and …
dementia in the elderly. Early detection of AD is critical for preventing brain damage and …