Adversarial Network-Based Classification for Alzheimer's Disease Using Multimodal Brain Images: A Critical Analysis

M Gupta, R Kumar, A Abraham - IEEE Access, 2024 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that represents a
significant and growing public health challenge. This work concisely summarizes AD …

Investigating Deep Learning for Early Detection and Decision-Making in Alzheimer's Disease: A Comprehensive Review

G Hcini, I Jdey, H Dhahri - Neural Processing Letters, 2024 - Springer
Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people
worldwide, making early detection essential for effective intervention. This review paper …

Enhancing paranasal sinus disease detection with AutoML: efficient AI development and evaluation via magnetic resonance imaging

RCT Cheong, S Jawad, A Adams, T Campion… - European Archives of …, 2024 - Springer
Purpose Artificial intelligence (AI) in the form of automated machine learning (AutoML) offers
a new potential breakthrough to overcome the barrier of entry for non-technically trained …

ERABiLNet: enhanced residual attention with bidirectional long short-term memory

K Seerangan, M Nandagopal, RR Nair… - Scientific Reports, 2024 - nature.com
Alzheimer's Disease (AD) causes slow death in brain cells due to shrinkage of brain cells
which is more prevalent in older people. In most cases, the symptoms of AD are mistaken as …

Unveiling Alzheimer's Disease Early: A Comprehensive Review of Machine Learning and Imaging Techniques

W Hechkel, A Helali - Archives of Computational Methods in Engineering, 2024 - Springer
Alzheimer's disease (AD) represents a growing global health concern, emphasizing the
urgent need for early detection and intervention strategies. This review article aims to …

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with …

I Arvidsson, O Strandberg, S Palmqvist… - Alzheimer's Research & …, 2024 - Springer
Abstract Background Predicting future Alzheimer's disease (AD)-related cognitive decline
among individuals with subjective cognitive decline (SCD) or mild cognitive impairment …

An effective Alzheimer's disease segmentation and classification using Deep ResUnet and Efficientnet

BS Rao, M Aparna, J Harikiran… - Journal of Biomolecular …, 2023 - Taylor & Francis
Alzheimer's disease (AD) is a degenerative neurologic condition that results in the
deterioration of several brain processes (eg memory loss). The most notable physical …

Identifying Alzheimer Disease Dementia Levels Using Machine Learning Methods

MG Hussain, Y Shiren - arXiv preprint arXiv:2311.01428, 2023 - arxiv.org
Dementia, a prevalent neurodegenerative condition, is a major manifestation of Alzheimer's
disease (AD). As the condition progresses from mild to severe, it significantly impairs the …

Dementia prediction with multimodal clinical and imaging data

NNBA Kubi, S Nazir - International Journal of Information Technology, 2024 - Springer
Dementia affects millions of people worldwide, and poses significant challenges due to its
irreversible nature and a lack of effective treatment options. Dementia has a considerable …

Implementasi Metode Convolutional Neural Network (CNN) Dalam Mendeteksi Jenis Sampah

D Darmawan - 2023 - repository.unja.ac.id
Sampah merupakan permasalahan yang terus meningkat di Indonesia. Jumlah sampah
yang terus bertambah setiap tahunnya menyebabkan banyak masalah, seperti pencemaran …