AIMC Topic: Algorithms

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A Learnable and Explainable Wavelet Neural Network for EEG Artifacts Detection and Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 16, 2024
Electroencephalography (EEG) artifacts are very common in clinical diagnosis and can heavily impact diagnosis. Manual screening of artifact events is labor-intensive with little benefit. Therefore, exploring algorithms for automatic detection and cla...
Electroencephalography Machine Learning Signal Processing, Computer-Assisted Algorithms Artifacts Reproducibility of Results Humans Wavelet Analysis Neural Networks, Computer
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A Strong and Simple Deep Learning Baseline for BCI Motor Imagery Decoding.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 16, 2024
We propose EEG-SimpleConv, a straightforward 1D convolutional neural network for Motor Imagery decoding in BCI. Our main motivation is to propose a simple and performing baseline that achieves high classification accuracy, using only standard ingredi...
Female Adult Male Humans Machine Learning Neural Networks, Computer Algorithms Movement Imagination Deep Learning Electroencephalography Brain-Computer Interfaces
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A Novel Method to Identify Mild Cognitive Impairment Using Dynamic Spatio-Temporal Graph Neural Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 16, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used in the identification of mild cognitive impairment (MCI) research, MCI patients are relatively at a higher risk of progression to Alzheimer's disease (AD). However, al...
Humans Aged Algorithms Magnetic Resonance Imaging Spatio-Temporal Analysis Male Brain Alzheimer Disease Deep Learning Middle Aged Neural Networks, Computer Female Cognitive Dysfunction Machine Learning
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Applying a community-engaged participatory machine learning model.

American journal of community psychology Sep 15, 2024
Although predictive algorithms have been described as the definitive solution to bias in health care, machine learning techniques may also propagate existing health inequities within the community context. However, there may be ways in which machine ...
Humans Machine Learning Algorithms Decision Making Community-Based Participatory Research
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AnyFace++: Deep Multi-Task, Multi-Domain Learning for Efficient Face AI.

Sensors (Basel, Switzerland) Sep 15, 2024
Accurate face detection and subsequent localization of facial landmarks are mandatory steps in many computer vision applications, such as emotion recognition, age estimation, and gender identification. Thanks to advancements in deep learning, numerou...
Deep Learning Emotions Algorithms Humans Face Female Male
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A Spatio-Temporal Capsule Neural Network with Self-Correlation Routing for EEG Decoding of Semantic Concepts of Imagination and Perception Tasks.

Sensors (Basel, Switzerland) Sep 15, 2024
Decoding semantic concepts for imagination and perception tasks (SCIP) is important for rehabilitation medicine as well as cognitive neuroscience. Electroencephalogram (EEG) is commonly used in the relevant fields, because it is a low-cost noninvasiv...
Imagination Semantics Brain-Computer Interfaces Perception Electroencephalography Signal Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Identification of Disulfidptosis-Related Genes in Ischemic Stroke by Combining Single-Cell Sequencing, Machine Learning Algorithms, and In Vitro Experiments.

Neuromolecular medicine Sep 15, 2024
BACKGROUND: Ischemic stroke (IS) is a severe neurological disorder with a pathogenesis that remains incompletely understood. Recently, a novel form of cell death known as disulfidptosis has garnered significant attention in the field of ischemic stro...
Animals Male Transcriptome Humans Machine Learning Algorithms Microglia Ischemic Stroke Cell Death Single-Cell Analysis Mice Nomograms
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Boundary-aware convolutional attention network for liver segmentation in ultrasound images.

Scientific reports Sep 15, 2024
Liver ultrasound is widely used in clinical practice due to its advantages of non-invasiveness, non-radiation, and real-time imaging. Accurate segmentation of the liver region in ultrasound images is essential for accelerating the auxiliary diagnosis...
Image Processing, Computer-Assisted Liver Algorithms Humans Deep Learning Ultrasonography Neural Networks, Computer
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Deep feature fusion with computer vision driven fall detection approach for enhanced assisted living safety.

Scientific reports Sep 15, 2024
Assisted living facilities cater to the demands of the elderly population, providing assistance and support with day-to-day activities. Fall detection is fundamental to ensuring their well-being and safety. Falls are frequent among older persons and ...
Humans Accidental Falls Assisted Living Facilities Algorithms Aged Deep Learning
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Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening.

International journal of laboratory hematology Sep 14, 2024
INTRODUCTION: VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displaying a large pleomorphic array of clinical and hematological features. Nevertheless, these criteria lack significance to discriminate VEXAS from othe...
Algorithms Female Male Humans Ubiquitin-Activating Enzymes Myelodysplastic Syndromes Skin Diseases, Genetic Deep Learning Neutrophils Mutation
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