AIMC Topic: Algorithms

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A Hybrid Artificial Intelligence System for Automated EEG Background Analysis and Report Generation.

IEEE journal of biomedical and health informatics
Electroencephalography (EEG) plays a crucial role in the diagnosis of various neurological disorders. However, small hospitals and clinics often lack advanced EEG signal analysis systems and are prone to misinterpretation in manual EEG reading. This ...

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...

Self-Supervised Multi-Scale Multi-Modal Graph Pool Transformer for Sellar Region Tumor Diagnosis.

IEEE journal of biomedical and health informatics
The sellar region tumor is a brain tumor that only exists in the brain sellar, which affects the central nervous system. The early diagnosis of the sellar region tumor subtypes helps clinicians better understand the best treatment and recovery of pat...

Prior Visual-Guided Self-Supervised Learning Enables Color Vignetting Correction for High-Throughput Microscopic Imaging.

IEEE journal of biomedical and health informatics
Vignetting constitutes a prevalent optical degradation that significantly compromises the quality of biomedical microscopic imaging. However, a robust and efficient vignetting correction methodology in multi-channel microscopic images remains absent ...

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...

Aceso-DSAL: Discovering Clinical Evidences From Medical Literature Based on Distant Supervision and Active Learning.

IEEE journal of biomedical and health informatics
Automatic extraction of valuable, structured evidence from the exponentially growing clinical trial literature can help physicians practice evidence-based medicine quickly and accurately. However, current research on evidence extraction has been limi...

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...

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...