AIMC Topic: Neural Networks, Computer

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Machine learning-based model for predicting the occurrence and mortality of nonpulmonary sepsis-associated ARDS.

Scientific reports
OBJECTIVE: The objective was to establish a machine learning-based model for predicting the occurrence and mortality of nonpulmonary sepsis-associated ARDS.

Partial prior transfer learning based on self-attention CNN for EEG decoding in stroke patients.

Scientific reports
The utilization of motor imagery-based brain-computer interfaces (MI-BCI) has been shown to assist stroke patients activate motor regions in the brain. In particular, the brain regions activated by unilateral upper limb multi-task are more extensive,...

Optimized robust learning framework based on big data for forecasting cardiovascular crises.

Scientific reports
Numerous Deep Learning (DL) scenarios have been developed for evolving new healthcare systems that leverage large datasets, distributed computing, and the Internet of Things (IoT). However, the data used in these scenarios tend to be noisy, necessita...

An ANN models cortical-subcortical interaction during post-stroke recovery of finger dexterity.

Journal of neural engineering
Finger dexterity, and finger individuation in particular, is crucial for human movement, and disruptions due to brain injury can significantly impact quality of life. Understanding the neurological mechanisms responsible for recovery is vital for eff...

MaskDGNets: Masked-attention guided dynamic graph aggregation network for event extraction.

PloS one
Considering that the traditional deep learning event extraction method ignores the correlation between word features and sequence information, it cannot fully explore the hidden associations between events and events and between events and primary at...

AFSleepNet: Attention-Based Multi-View Feature Fusion Framework for Pediatric Sleep Staging.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The widespread prevalence of sleep problems in children highlights the importance of timely and accurate sleep staging in the diagnosis and treatment of pediatric sleep disorders. However, most existing sleep staging methods rely on one-dimensional r...

Predicting Protein-Ligand Binding Affinity Using Fusion Model of Spatial-Temporal Graph Neural Network and 3D Structure-Based Complex Graph.

Interdisciplinary sciences, computational life sciences
The investigation of molecular interactions between ligands and their target molecules is becoming more significant as protein structure data continues to develop. In this study, we introduce PLA-STGCNnet, a deep fusion spatial-temporal graph neural ...

TV-Net: Temporal-Variable feature harmonizing Network for multivariate time series classification and interpretation.

Neural networks : the official journal of the International Neural Network Society
Multivariate time series classification (MTSC), which identifies categories of multiple sensor signals recorded in continuous time, is widely used in various fields such as transportation, finance, and medical treatment. The focused challenge remains...

BreathVisionNet: A pulmonary-function-guided CNN-transformer hybrid model for expiratory CT image synthesis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD) has high heterogeneity in etiologies and clinical manifestations. Expiratory Computed tomography (CT) can effectively assess air trapping, aiding in disease diagnosis. However, du...

MIU-Net: Advanced multi-scale feature extraction and imbalance mitigation for optic disc segmentation.

Neural networks : the official journal of the International Neural Network Society
Pathological myopia is a severe eye condition that can cause serious complications like retinal detachment and macular degeneration, posing a threat to vision. Optic disc segmentation helps measure changes in the optic disc and observe the surroundin...