Deep learning for neurodegenerative disorder (2016 to 2022): A systematic review

J Chaki, M Woźniak - Biomedical Signal Processing and Control, 2023 - Elsevier
A neurodegenerative disorder, such as Parkinson's, Alzheimer's, epilepsy, stroke, and
others, is a type of disease in which central nervous system cells stop working or die …

[HTML][HTML] Breast cancer classification from ultrasound images using probability-based optimal deep learning feature fusion

K Jabeen, MA Khan, M Alhaisoni, U Tariq, YD Zhang… - Sensors, 2022 - mdpi.com
After lung cancer, breast cancer is the second leading cause of death in women. If breast
cancer is detected early, mortality rates in women can be reduced. Because manual breast …

[HTML][HTML] Breast Cancer Classification Depends on the Dynamic Dipper Throated Optimization Algorithm

AA Alhussan, MM Eid, SK Towfek, DS Khafaga - Biomimetics, 2023 - mdpi.com
According to the American Cancer Society, breast cancer is the second largest cause of
mortality among women after lung cancer. Women's death rates can be decreased if breast …

Deep learning based pipelines for Alzheimer's disease diagnosis: a comparative study and a novel deep-ensemble method

A Loddo, S Buttau, C Di Ruberto - Computers in biology and medicine, 2022 - Elsevier
Background Alzheimer's disease is a chronic neurodegenerative disease that destroys brain
cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are …

Quantifying the impact of Pyramid Squeeze Attention mechanism and filtering approaches on Alzheimer's disease classification

B Yan, Y Li, L Li, X Yang, T Li, G Yang… - Computers in Biology and …, 2022 - Elsevier
Brain medical imaging and deep learning are important foundations for diagnosing and
predicting Alzheimer's disease. In this study, we explored the impact of different image …

Automated detection of Alzheimer's disease and mild cognitive impairment using whole brain MRI

FUR Faisal, GR Kwon - IEEE Access, 2022 - ieeexplore.ieee.org
Early diagnosis is critical for the development and success of interventions, and
neuroimaging is one of the most promising areas for early detection of Alzheimer's disease …

Alzheimer's disease diagnosis via multimodal feature fusion

Y Tu, S Lin, J Qiao, Y Zhuang, P Zhang - Computers in biology and …, 2022 - Elsevier
Alzheimer's disease (AD) is the most common neurodegenerative disorder in the elderly.
Early diagnosis of AD plays a vital role in slowing down the progress of AD because there is …

Hypergraph convolutional network for longitudinal data analysis in Alzheimer's disease

X Hao, J Li, M Ma, J Qin, D Zhang, F Liu… - Computers in Biology …, 2024 - Elsevier
Alzheimer's disease (AD) is an irreversible and progressive neurodegenerative disease.
Longitudinal structural magnetic resonance imaging (sMRI) data have been widely used for …

[HTML][HTML] OViTAD: Optimized vision transformer to predict various stages of Alzheimer's disease using resting-state fMRI and structural MRI data

S Sarraf, A Sarraf, DD DeSouza, JAE Anderson… - Brain Sciences, 2023 - mdpi.com
Advances in applied machine learning techniques for neuroimaging have encouraged
scientists to implement models to diagnose brain disorders such as Alzheimer's disease at …

[HTML][HTML] Unraveling Arrhythmias with Graph-Based Analysis: A Survey of the MIT-BIH Database

S Alinsaif - Computation, 2024 - mdpi.com
Cardiac arrhythmias, characterized by deviations from the normal rhythmic contractions of
the heart, pose a formidable diagnostic challenge. Early and accurate detection remains an …