AIMC Topic: Convolutional Neural Networks

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EEGConvNeXt: A novel convolutional neural network model for automated detection of Alzheimer's Disease and Frontotemporal Dementia using EEG signals.

Computer methods and programs in biomedicine Feb 8, 2025
BACKGROUND AND OBJECTIVE: Deep learning models have gained widespread adoption in healthcare for accurate diagnosis through the analysis of brain signals. Neurodegenerative disorders like Alzheimer's Disease (AD) and Frontotemporal Dementia (FD) are ...
Neural Networks, Computer Alzheimer Disease Humans Algorithms Frontotemporal Dementia Convolutional Neural Networks Electroencephalography Deep Learning Signal Processing, Computer-Assisted
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Exploring the impact of lenticels on the detection of soluble solids content in apples and pears using hyperspectral imaging and one-dimensional convolutional neural networks.

Food research international (Ottawa, Ont.) Feb 7, 2025
In this work, the effect of lenticels on the predictive performance of apple and pear soluble solids content (SSC) models developed based on hyperspectral imaging (HSI) at 380-1010 nm was investigated for the first time. Variations in the spectral pr...
Pyrus Convolutional Neural Networks Neural Networks, Computer Hyperspectral Imaging Principal Component Analysis Algorithms Discriminant Analysis Calibration Least-Squares Analysis Fruit Malus
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Multimodal convolutional neural networks for the prediction of acute kidney injury in the intensive care.

International journal of medical informatics Feb 4, 2025
Increased monitoring of health-related data for ICU patients holds great potential for the early prediction of medical outcomes. Research on whether the use of clinical notes and concepts from knowledge bases can improve the performance of prediction...
Creatinine Critical Care Intensive Care Units Male Humans Convolutional Neural Networks Neural Networks, Computer Acute Kidney Injury
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Computer-aided cholelithiasis diagnosis using explainable convolutional neural network.

Scientific reports Feb 4, 2025
Accurate and precise identification of cholelithiasis is essential for saving the lives of millions of people worldwide. Although several computer-aided cholelithiasis diagnosis approaches have been introduced in the literature, their use is limited ...
Humans Neural Networks, Computer Algorithms Diagnosis, Computer-Assisted Cholelithiasis Convolutional Neural Networks Ultrasonography
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Convolutional Neural Networks Assisted Peak Classification in Targeted LC-HRMS/MS for Equine Doping Control Screening Analyses.

Analytical chemistry Feb 3, 2025
Doping control screening analyses usually involve visual inspection of extracted ion chromatograms (EIC) by a trained analytical chemist, followed by further investigations if needed. This task is both highly repetitive and time-consuming, given the ...
Doping in Sports Deep Learning Convolutional Neural Networks Discriminant Analysis Chromatography, High Pressure Liquid Tandem Mass Spectrometry Horses Neural Networks, Computer Animals
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Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.

Scientific reports Feb 3, 2025
Previous deep learning-based brain network research has made significant progress in understanding the pathophysiology of schizophrenia. However, it ignores the three-dimensional spatial characteristics of EEG signals and cannot dynamically learn the...
Algorithms Female Adult Humans Electroencephalography Schizophrenia Nerve Net Male Convolutional Neural Networks Models, Neurological Graph Neural Networks
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Optimization of sparse-view CT reconstruction based on convolutional neural network.

Medical physics Feb 2, 2025
BACKGROUND: Sparse-view CT shortens scan time and reduces radiation dose but results in severe streak artifacts due to insufficient sampling data. Deep learning methods can now suppress these artifacts and improve image quality in sparse-view CT reco...
Convolutional Neural Networks Image Processing, Computer-Assisted Neural Networks, Computer Artifacts Tomography, X-Ray Computed Deep Learning Humans
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Enhanced electroencephalogram signal classification: A hybrid convolutional neural network with attention-based feature selection.

Brain research Feb 2, 2025
Accurate recognition and classification of motor imagery electroencephalogram (MI-EEG) signals are crucial for the successful implementation of brain-computer interfaces (BCI). However, inherent characteristics in original MI-EEG signals, such as non...
Imagination Attention Brain-Computer Interfaces Brain Male Deep Learning Convolutional Neural Networks Electroencephalography Signal Processing, Computer-Assisted Humans Neural Networks, Computer
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Multi-branch convolutional neural network with cross-attention mechanism for emotion recognition.

Scientific reports Feb 1, 2025
Research on emotion recognition is an interesting area because of its wide-ranging applications in education, marketing, and medical fields. This study proposes a multi-branch convolutional neural network model based on cross-attention mechanism (MCN...
Humans Electroencephalography Neural Networks, Computer Convolutional Neural Networks Algorithms Attention Emotions
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Optimizing Skin Cancer Diagnosis: A Modified Ensemble Convolutional Neural Network for Classification.

Microscopy research and technique Jan 31, 2025
Skin cancer is recognized as one of the most harmful cancers worldwide. Early detection of this cancer is an effective measure for treating the disease efficiently. Traditional skin cancer detection methods face scalability challenges and overfitting...
Humans Sensitivity and Specificity Deep Learning Convolutional Neural Networks Neural Networks, Computer Algorithms Skin Neoplasms
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