AIMC Topic: Neural Networks, Computer

Clear Filters Showing 2011 to 2020 of 31376 articles

Deep Gated Neural Network With Self-Attention Mechanism for Survival Analysis.

IEEE journal of biomedical and health informatics
Survival analysis is commonly used to model the time distributions of the first occurrences of events of interest, and it has widespread medical applications. Many previous studies learned the relationship between risk and covariates by making strong...

LGG-NeXt: A Next Generation CNN and Transformer Hybrid Model for the Diagnosis of Alzheimer's Disease Using 2D Structural MRI.

IEEE journal of biomedical and health informatics
Incurable Alzheimer's disease (AD) plagues many elderly people and families. It is important to accurately diagnose and predict it at an early stage. However, the existing methods have shortcomings, such as inability to learn local and global informa...

Feature Separation in Diffuse Lung Disease Image Classification by Using Evolutionary Algorithm-Based NAS.

IEEE journal of biomedical and health informatics
In the field of diagnosing lung diseases, the application of neural networks (NNs) in image classification exhibits significant potential. However, NNs are considered "black boxes," making it difficult to discern their decision-making processes, ther...

LKAN: LLM-Based Knowledge-Aware Attention Network for Clinical Staging of Liver Cancer.

IEEE journal of biomedical and health informatics
Clinical staging of liver cancer (CSoLC), an important indicator for evaluating primary liver cancer (PLC), is key in the diagnosis, treatment, and rehabilitation of liver cancer. In China, the current CSoLC adopts the China liver cancer (CNLC) stagi...

TrustEMG-Net: Using Representation-Masking Transformer With U-Net for Surface Electromyography Enhancement.

IEEE journal of biomedical and health informatics
Surface electromyography (sEMG) is a widely employed bio-signal that captures human muscle activity via electrodes placed on the skin. Several studies have proposed methods to remove sEMG contaminants, as non-invasive measurements render sEMG suscept...

Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification.

IEEE journal of biomedical and health informatics
Fundus disease is a complex and universal disease involving a variety of pathologies. Its early diagnosis using fundus images can effectively prevent further diseases and provide targeted treatment plans for patients. Recent deep learning models for ...

DC-ASTGCN: EEG Emotion Recognition Based on Fusion Deep Convolutional and Adaptive Spatio-Temporal Graph Convolutional Networks.

IEEE journal of biomedical and health informatics
Thanks to advancements in artificial intelligence and brain-computer interface (BCI) research, there has been increasing attention towards emotion recognition techniques based on electroencephalogram (EEG) recently. The complexity of EEG data poses a...

A Novel Hierarchical Cross-Stream Aggregation Neural Network for Semantic Segmentation of 3-D Dental Surface Models.

IEEE transactions on neural networks and learning systems
Accurate teeth delineation on 3-D dental models is essential for individualized orthodontic treatment planning. Pioneering works like PointNet suggest a promising direction to conduct efficient and accurate 3-D dental model analyses in end-to-end lea...

An Efficient Graph Learning System for Emotion Recognition Inspired by the Cognitive Prior Graph of EEG Brain Network.

IEEE transactions on neural networks and learning systems
Benefiting from the high-temporal resolution of electroencephalogram (EEG), EEG-based emotion recognition has become one of the hotspots of affective computing. For EEG-based emotion recognition systems, it is crucial to utilize state-of-the-art lear...

Robust Sensory Information Reconstruction and Classification With Augmented Spikes.

IEEE transactions on neural networks and learning systems
Sensory information recognition is primarily processed through the ventral and dorsal visual pathways in the primate brain visual system, which exhibits layered feature representations bearing a strong resemblance to convolutional neural networks (CN...