BACKGROUND: Automated whole-brain delineation (WBD) techniques often struggle to generalize across pre-clinical studies due to variations in animal models, magnetic resonance imaging (MRI) scanners, and tissue contrasts. We developed a 3D U-Net neura...
BACKGROUND AND OBJECTIVE: The COVID-19 pandemic plays a significant roles in the global health, highlighting the imperative for effective management of post-recovery symptoms. Within this context, Ground Glass Opacity (GGO) in lung computed tomograph...
This study aims to optimize ibuprofen-based Drug Delivery Systems (DDSs) to address their short half-life and enhance controlled release. Advanced machine learning techniques, including Artificial Neural Networks, Random Forest, and CatBoost, were em...
This study proposes a method for detecting trace quinolone antibiotics in milk using a ternary composite surface-enhanced Raman spectroscopy (SERS) substrate. It combines chemometric algorithms and deep learning models to achieve qualitative and quan...
Tractography uses diffusion Magnetic Resonance Imaging (dMRI) to noninvasively reconstruct brain white matter (WM) tracts, with Convolutional Neural Network (CNNs) like U-Net significantly advancing accuracy in medical image segmentation. This work p...
BACKGROUND: The rising prevalence of dementia necessitates a scalable solution to cognitive screening. Paper-based cognitive screening examinations are well-validated but minimally scalable. If a digital cognitive screening examination could replicat...
BACKGROUND: In acute neck infections, magnetic resonance imaging (MRI) shows retropharyngeal edema (RPE), which is a prognostic imaging biomarker for a severe course of illness. This study aimed to develop a deep learning-based algorithm for the auto...
Neural networks : the official journal of the International Neural Network Society
Jun 18, 2025
Few-shot knowledge graph completion (FKGC) aims to predict missing triples for unseen relations by observing several associated reference entity pairs. Current methods address this task by learning relation prototypes from the direct neighborhoods of...
Neural networks : the official journal of the International Neural Network Society
Jun 18, 2025
Under the framework of backstepping theory, dealing with the non-differentiable problem of virtual control signals caused by sensor output triggering is difficult. Meanwhile, it is of great practical significance to consider problems of output trigge...
OBJECTIVES: The purpose of this study was to automatically segment and quantify the median nerve and carpal arch from ultrasound images using convolutional neural network (CNN).
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