Alzheimer's disease (AD) is a progressive illness that can cause behavioural abnormalities, personality changes, and memory loss. Early detection helps with future planning for both the affected person and caregivers. Thus, an innovative hybrid Deep ...
To solve the problems of existing encrypted traffic classification methods, such as the need for large-scale training data, high computational costs, and poor generalization ability, an encrypted traffic classification method based on autoencoders an...
This study presents a novel multi-sensor fusion strategy for discriminating wines made from eight different raw materials using identical brewing processes. Aroma and taste signals were collected using a broad-spectrum electronic nose and noble metal...
. The compound muscle action potential (CMAP) scan contains a muscle's detailed stimulus-activation information and thereby can be used for motor unit number estimation (MUNE). Due to the challenges in accurately obtaining the motor unit numbers from...
The automatic detection of Alzheimer's disease (AD) using 3D volumetric MRI data is a complex, multi-domain challenge that has traditionally been addressed by training classical convolutional neural networks (CNNs). With the rise of quantum computing...
Journal of chemical information and modeling
Sep 16, 2025
Designing novel high-performance donor and acceptor molecules is essential for improving the power conversion efficiency (PCE) of organic solar cells (OSCs). However, conventional experimental methods for developing new materials are often time-consu...
Cervical cancer remains a significant cause of female mortality worldwide, primarily due to abnormal cell growth in the cervix. This study proposes an automated classification method to enhance detection accuracy and efficiency, addressing contrast a...
This study addresses the pressing global health burden of mosquito-borne diseases by investigating the application of Convolutional Neural Networks (CNNs) for mosquito species identification using wing images. Conventional identification methods are ...
BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is common in adults while myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is rare. Our previous machine-learning algorithm, using clinical variables, ≤6 brain lesions, and no ...
Purpose Prediction of the ectasia screening index, an estimator provided by the Casia2 instrument for identifying keratoconus, from raw optical coherence tomography data using convolutional neural networks. Methods Three convolutional neural networks...
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