Alzheimer's Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review

MG Alsubaie, S Luo, K Shaukat - Machine Learning and Knowledge …, 2024 - mdpi.com
Alzheimer's disease (AD) is a pressing global issue, demanding effective diagnostic
approaches. This systematic review surveys the recent literature (2018 onwards) to …

Advancements in Alzheimer's disease classification using deep learning frameworks for multimodal neuroimaging: A comprehensive review

P Upadhyay, P Tomar, SP Yadav - Computers and Electrical Engineering, 2024 - Elsevier
Over the past years, Alzheimer's disease has emerged as a serious concern for people's
health. Researchers are facing challenges in effectively categorizing and diagnosing the …

Advancements in 3D printing materials: A comparative analysis of performance and applications

R Subramani, MA Mustafa, GK Ghadir… - Applied Chemical …, 2024 - ace.as-pub.com
Abstract 3D printing has rapidly evolved and matured in recent years, with a key factor being
the improvement in printing materials. This paper compares the performance and …

Exploring the use of Biodegradable Polymer Materials in Sustainable 3D Printing

R Subramani, MA Mustafa, GK Ghadir… - Applied Chemical …, 2024 - ace.as-pub.com
The use of biodegradable materials in 3D printing has gained attention due to its potential in
addressing environmental concerns in the manufacturing industry. This paper aims to …

Machine Learning Techniques for Analysing Security Practises in Electronic Health Records

BK Saraswat, A Saxena… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Electronic health statistics (EHR) security is essential because the fitness information saved
and transmitted in these data is exclusive. Suppose you want to ensure the proper safety of …

The smart detection of neuro-pathological effects of alzheimer patients using neural networks

B Namatherdhala, A Ganesh, N Memon… - … For Smart Nation …, 2023 - ieeexplore.ieee.org
Neural networks have been increasingly utilized for smart detection of neuro-pathological
effects of patients with Alzheimer's Disease. By leveraging the vast amounts of data …

Multi-scale object detection and classification using machine learning and image processing

N Yuvaraj, K Rajput, K Suganyadevi… - … Conference on Data …, 2024 - ieeexplore.ieee.org
Multi-scale object detection and category has grown to be important duties in numerous
domain names, including laptop imaginative and prescient, autonomous driving, and …

[PDF][PDF] Original Research article Surface metamorphosis techniques for sustainable polymers: Optimizing material performance and environmental impact

N Nagabhooshanam, J Subramanian, VK Selvaraj - 2024 - researchgate.net
The transition to sustainable polymers is crucial for reducing the environmental footprint of
additive manufacturing, particularly in fused deposition modeling (FDM). This study …

[HTML][HTML] ALSA-3: Customized CNN model through ablation study for Alzheimer's disease classification

M Assaduzzaman, M Dutta, A Saha, SG Paul - Informatics in Medicine …, 2024 - Elsevier
Abstract Alzheimer's disease (AD), a prevalent neurological condition, poses a multifaceted
challenge affecting millions worldwide. It demands diverse solutions, both pharmaceutical …

Spectral graph convolutional neural network for Alzheimer's disease diagnosis and multi-disease categorization from functional brain changes in magnetic resonance …

H Alharbi, RA Juanatas, A Al Hejaili… - Frontiers in …, 2024 - frontiersin.org
Alzheimer's disease (AD) is a progressive neurological disorder characterized by the
gradual deterioration of cognitive functions, leading to dementia and significantly impacting …