AIMC Topic: Algorithms

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Novel approach for AI-based NO emission reduction in biological wastewater treatment relying on genetic algorithms and neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
The potential of measurement-based control strategies for achieving lower NO emissions in biological wastewater treatment is limited due to strong temporal variations in NO emissions and a lack of measurement data regarding influencing parameters. To...

Improving Foundation Model for Endoscopy Video Analysis via Representation Learning on Long Sequences.

IEEE journal of biomedical and health informatics
Recent advancements in endoscopy video analysis have relied on the utilization of relatively short video clips extracted from longer videos or millions of individual frames. However, these approaches tend to neglect the domain-specific characteristic...

CrossConvPyramid: Deep Multimodal Fusion for Epileptic Magnetoencephalography Spike Detection.

IEEE journal of biomedical and health informatics
Magnetoencephalography (MEG) is a vital non-invasive tool for epilepsy analysis, as it captures high-resolution signals that reflect changes in brain activity over time. The automated detection of epileptic spikes within these signals can significant...

Unsupervised Domain Adaptation With Synchronized Self-Training for Cross- Domain Motor Imagery Recognition.

IEEE journal of biomedical and health informatics
Robust decoding performance is essential for the practical deployment of brain-computer interface (BCI) systems. Existing EEG decoding models often rely on large amounts of annotated data collected through specific experimental setups, which fail to ...

A Distributed Neural Network Architecture for Dynamic Sensor Selection With Application to Bandwidth-Constrained Body-Sensor Networks.

IEEE journal of biomedical and health informatics
We propose a dynamic sensor selection approach for deep neural networks (DNNs), which is able to derive an optimal sensor subset selection for each specific input sample instead of a fixed selection for the entire dataset. This dynamic selection is j...

MHFNet: A Multimodal Hybrid-Embedding Fusion Network for Automatic Sleep Staging.

IEEE journal of biomedical and health informatics
Scoring sleep stages is essential for evaluating the status of sleep continuity and comprehending its structure. Despite previous attempts, automating sleep scoring remains challenging. First, most existing works did not fuse local and global tempora...

MLDA-Net: Multi-Level Deep Aggregation Network for 3D Nuclei Instance Segmentation.

IEEE journal of biomedical and health informatics
Segmentation of cell nuclei from three-dimensional (3D) volumetric fluorescence microscopy images is crucial for biological and clinical analyses. In recent years, convolutional neural networks have become the reliable 3D medical image segmentation s...

Anomaly Detection in Electronic Health Records Across Hospital Networks: Integrating Machine Learning With Graph Algorithms.

IEEE journal of biomedical and health informatics
In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to make informed decisions regarding their patients in various clinical domains. Consequently, the dependability of the health information technology (HIT) ...

Predicting Drug-miRNA Associations Combining SDNE with BiGRU.

IEEE journal of biomedical and health informatics
It is well recognized that abnormal miRNA expression can result in drug resistance and pose a challenge to miRNA-based treatments. However, the drug-miRNA associations (DMA) are still incompletely understood. Conventional biological experiments have ...

Progressive Distillation With Optimal Transport for Federated Incomplete Multi-Modal Learning of Brain Tumor Segmentation.

IEEE journal of biomedical and health informatics
Multi-modal Magnetic Resonance Imaging (MRI) provide sufficient complementary information for brain tumor segmentation, however, most current approaches rely on complete modalities and may collapse with incomplete modalities. Moreover, most existing ...