Results 141 to 150 of about 84,208 (297)

Graph-based vision transformer with sparsity for training on small datasets from scratch

Scientific Reports
Vision Transformers (ViTs) have achieved impressive results in large-scale image classification. However, when training from scratch on small datasets, there is still a significant performance gap between ViTs and Convolutional Neural Networks (CNNs ...
Peng Li, Lu Huang, Jin Li, Haiyan Yan, Dongjing Shan   +4 more
doaj   +1 more source

Anomaly detection in graph databases using graph neural networks: Identifying unusual patterns in graphs

Egyptian Informatics Journal
Anomaly detection in graph-structured data is a critical task in various applications, including social networks, fraud detection, and educational platforms.
Ismail Chetoui, Essaid El Bachari, Mohamed El Adnani, Mohamed Ouhssini   +3 more
doaj   +1 more source

Aqueous Two‐Phase Bioinks for Discrete Packing and Compartmentalization of 3D Bioprinted Cells

Advanced Healthcare Materials, EarlyView.
Aqueous two‐phase systems (ATPS) enable the formation of biomimetic interfaces crucial for tissue engineering. However, clinical translation remains limited by the challenge of precisely controlling cellular compartmentalization. Here, we developed ATPS biomaterial inks for 3D bioprinting allowing tuneable droplet formation via NaCl modulation.
Martina Marcotulli, Arianna Iacomino, Federico Serpe, Lucia Iafrate, Marco Bastioli, Giorgia Montalbano, Michele D'Orazio, Biagio Palmisano, Silvia Franco, Arianna Mencattini, Roberta Angelini, Eugenio Martinelli, Alessandro Corsi, Mara Riminucci, Giancarlo Ruocco, Chiara Scognamiglio, Andrea Barbetta, Gianluca Cidonio   +17 more
wiley   +1 more source

Comparative Analysis of Multi-Omics Integration Using Graph Neural Networks for Cancer Classification

IEEE Access
Recent studies on integrating multiple omics data highlighted the potential to advance our understanding of the cancer disease process. Computational models based on graph neural networks and attention-based architectures have demonstrated promising ...
Fadi Alharbi, Aleksandar Vakanski, Boyu Zhang, Murtada K. Elbashir, Mohanad Mohammed   +4 more
doaj   +1 more source

Soft Neural Interfaces for Circuit‐Level Analysis of Magnetogenetic Deep Brain Stimulation in Parkinson's Disease Models

Advanced Healthcare Materials, EarlyView.
ABSTRACT Magnetogenetic deep brain stimulation (MG‐DBS) represents a wireless neuromodulation that has demonstrated long‐lasting behavioral benefits in Parkinson's disease models. However, the circuit‐level mechanisms underlying these therapeutic effects have remained uncharacterized due to limitations of conventional neural interfaces.
Jakyoung Lee, Yeongdo Lee, Enji Kim, Hunkyu Seo, Myoungjae Oh, Hanho Joo, Somin Lee, Jae‐Hyun Lee, Hyun Ho Jung, Minsuk Kwak, Jang‐Ung Park   +10 more
wiley   +1 more source

Photothermal‐Activated Antibacterial Amyloid‐Polyphenol‐Iron Hydrogels for Synergistic Wound Healing

Advanced Healthcare Materials, EarlyView.
We report a thermally triggered supramolecular hydrogel (LTFe) formed by Fe3+ and tannic acid on lysozyme amyloid fibrils. Fe3+ enables rapid gelation and photothermal transduction with an efficiency of 88.56%. The LTFe hydrogel exhibits excellent biocompatibility, potent antibacterial activity against E. coli and S.
Di Wu, Jiangtao Zhou, Yang Shen, Qiyao Sun, Tong Li, Xiaoyang Zou, Bin Liu, Hongshan Liang, Raffaele Mezzenga   +8 more
wiley   +1 more source

A Data Driven Review of In Vitro Electrical and Mechanical Stimulation for Post‐Acute Phase Wound Healing

Advanced Healthcare Materials, EarlyView.
This review examines how in vitro electrical and mechanical stimulation modulates wound healing in fibroblasts and keratinocytes. Analyzing over 560 experimental data points, we relate stimulation parameters to proliferation and migration outcomes, evaluate platform designs, and highlight the need for multi‐parameter optimization to advance targeted ...
Matthew K. Burgess, Ellen F. Marsh, Veronica M. Lucian, Malavika Nair   +3 more
wiley   +1 more source

A Hybrid Graph Neural Network Model for Predicting Cyber Attacks From Heterogeneous and Dynamic Network Data

IEEE Access
With valuable data constantly under attack, reactive security measures are no longer sufficient. Predicting cyber threats before they emerge is crucial. Cyberattacks do not occur randomly; they have a systematic underlying pattern.
Mucahit Soylu, Resul Das
doaj   +1 more source

Graph Neural Networks Exploration

, 2023
Táto práca sa venuje rozboru metód grafových neurónových sietí pre klasifikáciu vrcholov a grafov. Skúma súčasné knižnice na prácu s grafovými neurónovými sieťami ako StellarGraph, PyTorch Geometric a DGL.
Barbara Bobeničová
core  

A Systematic Study of GelMA‐Carbopol Bioinks for High‐Fidelity Extrusion 3D Bioprinting at Physiological Temperatures

Advanced Healthcare Materials, EarlyView.
Gonzalez Martinez and collaborators develop a strategy to formulate high performance GelMA‐based bioinks with low solids contents. The resulting bioinks enable 3D bioprinting at 37 °C of high‐fidelity structures with tunable mechanical properties that support high cell viability and function.
David A. González‐Martínez, Aidee V. Arizpe Tafoya, Eduardo González‐Martínez, Mabel Barreiro Carpio, Laura Daniela Serrano Andrade, Christopher T. N. Chow, Mohammadhossein Dabaghi, Jeremy A. Hirota, Jose M. Moran‐Mirabal   +8 more
wiley   +1 more source