Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using a...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 7, 2025
Diffusion-weighted imaging (DWI) is widely applied in tumor diagnosis by measuring the diffusion of water molecules. To increase the sensitivity to tumor identification, faithful high b-value DWI images are expected by setting a stronger strength of ...
Serum alanine aminotransferase (ALT) is one of the most sensitive indicators of liver function and is crucial in diagnosing acute liver injury (ALI). However, its widespread clinical application is limited due to expensive equipment, detection delays...
This study introduces a new methodology for developing graphical feature maps using weighted artificial neural networks (w-ANNs) and demonstrates its application in the classification of loquat juice varieties (namely loquat_baisha and loquat_hongsha...
Biliary tract cancer is associated with distinct metabolic alterations, particularly in lipid metabolism. This study aimed to classify biliary tract cancer cells automatically based on lipid droplet (LD) characteristics using three-dimensional (3D) o...
INTRODUCTION AND AIMS: The overlapping characteristics of oral lichen planus (OLP), a chronic oral mucosal inflammatory condition, with those of other oral lesions, present diagnostic challenges. Large language models (LLMs) with integrated computer-...
Cross-corpus speech emotion recognition (CCSER) aims to develop robust models capable of accurately identifying a speaker's emotional state across diverse datasets. This task is challenged by variations in dataset characteristics, such as differences...
The ever-increasing availability of high-throughput DNA sequences and the development of numerous computational methods have led to considerable advances in our understanding of the evolutionary and demographic history of populations. Several demogra...
The nexus of quantum computing and machine learning─quantum machine learning─offers the potential for significant advancements in chemistry. This Review specifically explores the potential of quantum neural networks on gate-based quantum computers wi...
OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. This study evaluates the efficacy of deep learning algorithms...
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