Physical and engineering sciences in medicine
Jun 11, 2024
Alzheimer's disease (AD) is a progressive and incurable neurologi-cal disorder with a rising mortality rate, worsened by error-prone, time-intensive, and expensive clinical diagnosis methods. Automatic AD detection methods using hand-crafted Electroe...
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jun 11, 2024
INTRODUCTION: Most people with Alzheimer's disease and related dementia (ADRD) also suffer from two or more chronic conditions, known as multiple chronic conditions (MCC). While many studies have investigated the MCC patterns, few studies have consid...
The identification of diagnostic and therapeutic biomarkers for Alzheimer's Disease (AD) remains a crucial area of research. In this study, utilizing the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm, we identified RHBDF2 and TNFRSF1...
Tensor-based representations are being increasingly used to represent complex data types such as imaging data, due to their appealing properties such as dimension reduction and the preservation of spatial information. Recently, there is a growing lit...
IEEE journal of biomedical and health informatics
Jun 6, 2024
Alzheimer's disease (AD) is a neurodegenerative disorder that can cause a significant impairment in physical and cognitive functions. Gait disturbances are also reported as a symptom of AD. Previous works have used Convolutional Neural Networks (CNNs...
The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these...
BACKGROUND: Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic da...
IEEE transactions on neural networks and learning systems
Jun 3, 2024
Learning brain effective connectivity networks (ECN) from functional magnetic resonance imaging (fMRI) data has gained much attention in recent years. With the successful applications of deep learning in numerous fields, several brain ECN learning me...
IEEE transactions on neural networks and learning systems
Jun 3, 2024
The detection and segmentation of stained cells and nuclei are essential prerequisites for subsequent quantitative research for many diseases. Recently, deep learning has shown strong performance in many computer vision problems, including solutions ...
IEEE transactions on neural networks and learning systems
Jun 3, 2024
Alzheimer's disease (AD) is a neurodegenerative disease with profound pathogenetic causes. Imaging genetic data analysis can provide comprehensive insights into its causes. To fully utilize the multi-level information in the data, this article propos...
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