AIMC Topic: Neural Networks, Computer

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Author name disambiguation based on heterogeneous graph neural network.

PloS one
With the dramatic increase in the number of published papers and the continuous progress of deep learning technology, the research on name disambiguation is at a historic peak, the number of paper authors is increasing every year, and the situation o...

Label-free rapid antimicrobial susceptibility testing with machine-learning based dynamic holographic laser speckle imaging.

Biosensors & bioelectronics
Antimicrobial resistance (AMR) presents a significant global challenge, creating an urgent need for rapid and sensitive antimicrobial susceptibility testing (AST) methods to guide timely treatment decisions. Traditional AST techniques, such as broth ...

Interpretable modality-specific and interactive graph convolutional network on brain functional and structural connectomes.

Medical image analysis
Both brain functional connectivity (FC) and structural connectivity (SC) provide distinct neural mechanisms for cognition and neurological disease. In addition, interactions between SC and FC within distributed association regions are related to alte...

Exploring the values underlying machine learning research in medical image analysis.

Medical image analysis
Machine learning has emerged as a crucial tool for medical image analysis, largely due to recent developments in deep artificial neural networks addressing numerous, diverse clinical problems. As with any conceptual tool, the effective use of machine...

Exploring temporal information dynamics in Spiking Neural Networks: Fast Temporal Efficient Training.

Journal of neuroscience methods
BACKGROUND: Spiking Neural Networks (SNNs) hold significant potential in brain simulation and temporal data processing. While recent research has focused on developing neuron models and leveraging temporal dynamics to enhance performance, there is a ...

Predicting social anxiety disorder based on communication logs and social network data from a massively multiplayer online game: Using a graph neural network.

Psychiatry and clinical neurosciences
AIM: Social anxiety disorder (SAD) is a mental disorder that requires early detection and treatment. However, some individuals with SAD avoid face-to-face evaluations, which leads to delayed detection. We aim to predict individuals with SAD based on ...

CephTransX: An attention enhanced feature fusion network leveraging neighborhood rough set approach for cephalometric landmark prediction.

Computers in biology and medicine
The convergence of medical imaging, computer vision, and orthodontics has made automatic cephalometric landmark detection a pivotal area of research. Accurate cephalometric analysis is crucial in orthodontics, orthognathic and maxillofacial surgery f...

MRI-Based Meningioma Firmness Classification Using an Adversarial Feature Learning Approach.

Sensors (Basel, Switzerland)
The firmness of meningiomas is a critical factor that impacts the surgical approach recommended for patients. The conventional approaches that couple image processing techniques with radiologists' visual assessments of magnetic resonance imaging (MRI...

Hybrid CNN-GRU Models for Improved EEG Motor Imagery Classification.

Sensors (Basel, Switzerland)
Brain-computer interfaces (BCIs) based on electroencephalography (EEG) enable neural activity interpretation for device control, with motor imagery (MI) serving as a key paradigm for decoding imagined movements. Efficient feature extraction from raw ...

Assessing the effectiveness of long short-term memory and artificial neural network in predicting daily ozone concentrations in Liaocheng City.

Scientific reports
Ozone pollution affects food production, human health, and the lives of individuals. Due to rapid industrialization and urbanization, Liaocheng has experienced increasing of ozone concentration over several years. Therefore, ozone has become a major ...