AIMC Topic: Alzheimer Disease

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EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models.

Scientific reports
In the context of lifestyle changes, stress and other environmental factors have resulted in the sudden hike in dementia globally. This necessitates investigations with respect to every horizon of the due cause for it; further on, the diagnosis and t...

Enhancing Neurodegenerative Disease Diagnosis Through Confidence-Driven Dynamic Spatio-Temporal Convolutional Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dynamic brain networks are more effective than static networks in characterizing the evolving patterns of brain functional connectivity, making them a more promising tool for diagnosing neurodegenerative diseases. However, existing classification met...

Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.

American journal of Alzheimer's disease and other dementias
To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). A recursive partitioning tree model was developed using ARMADA data and the NIH Toolbox, a...

Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper proposed a Brain-Region-Selected graph convolutional network (BRS-GCN). In order to effectively identify the most significant biomarkers associated w...

Ensemble Learning-Based Alzheimer's Disease Classification Using Electroencephalogram Signals and Clock Drawing Test Images.

Sensors (Basel, Switzerland)
Ensemble learning (EL), a machine learning technique that combines the results of multiple learning algorithms to obtain predicted values, aims to achieve better predictive performance than a single learning algorithm alone. Machine learning techniqu...

Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.

IEEE transactions on neural networks and learning systems
Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the impo...

Ge-SAND: an explainable deep learning-driven framework for disease risk prediction by uncovering complex genetic interactions in parallel.

BMC genomics
BACKGROUND: Accurate genetic risk prediction and understanding the mechanisms underlying complex diseases are essential for effective intervention and precision medicine. However, current methods often struggle to capture the intricate and subtle gen...

A novel diagnosis method utilizing MDBO-SVM and imaging genetics for Alzheimer's disease.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) is the most common neurodegenerative disorder, yet its underlying mechanisms remain elusive. Early and accurate diagnosis is crucial for timely intervention and disease management. In this paper, a multi-strategy improved dun...

Therapeutic potential of enzymes, neurosteroids, and synthetic steroids in neurodegenerative disorders: A critical review.

The Journal of steroid biochemistry and molecular biology
Neurodegenerative disorders present a significant challenge to healthcare systems, mainly due to the limited availability of effective treatment options to halt or reverse disease progression. Endogenous steroids synthesized in the central nervous sy...

A review of multimodal fusion-based deep learning for Alzheimer's disease.

Neuroscience
Alzheimer's Disease (AD) as one of the most prevalent neurodegenerative disorders worldwide, characterized by significant memory and cognitive decline in its later stages, severely impacting daily lives. Consequently, early diagnosis and accurate ass...