AIMC Topic: Convolutional Neural Networks

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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.

PloS one Feb 13, 2025
This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. Firstly, the data collected in this study come fr...
Random Forest Biomechanical Phenomena Running Convolutional Neural Networks Humans Support Vector Machine Athletes Pattern Recognition, Automated Machine Learning Track and Field Computer Simulation
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Classification of fundus autofluorescence images based on macular function in retinitis pigmentosa using convolutional neural networks.

Japanese journal of ophthalmology Feb 12, 2025
PURPOSE: To determine whether convolutional neural networks (CNN) can classify the severity of central vision loss using fundus autofluorescence (FAF) images and color fundus images of retinitis pigmentosa (RP), and to evaluate the utility of those i...
Retinitis Pigmentosa Visual Acuity Tomography, Optical Coherence Fundus Oculi Visual Fields Fluorescein Angiography Humans Macula Lutea Female Middle Aged Neural Networks, Computer Aged Convolutional Neural Networks Retrospective Studies Adolescent Young Adult Adult Male
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Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

International journal of molecular sciences Feb 11, 2025
The prediction of circular RNA (circRNA)-drug associations plays a crucial role in understanding disease mechanisms and identifying potential therapeutic targets. Traditional methods often struggle to cope with the complexity of heterogeneous network...
Autoencoder RNA, Circular Convolutional Neural Networks Computational Biology Humans Pharmaceutical Preparations Neural Networks, Computer Algorithms
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An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Scientific reports Feb 9, 2025
Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strateg...
Female Adult Breast Neoplasms Humans Neural Networks, Computer Convolutional Neural Networks ROC Curve Mammography Receptor, ErbB-2 Biomarkers, Tumor Middle Aged Deep Learning Receptors, Estrogen Receptors, Progesterone
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DKCN-Net: Deep kronecker convolutional neural network-based lung disease detection with federated learning.

Computational biology and chemistry Feb 8, 2025
In the healthcare field, lung disease detection techniques based on deep learning (DL) are widely used. However, achieving high stability while maintaining privacy remains a challenge. To address this, this research employs Federated Learning (FL), e...
Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Federated Learning Convolutional Neural Networks Humans Lung Diseases
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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 ...
Humans Neural Networks, Computer Convolutional Neural Networks Algorithms Electroencephalography Alzheimer Disease Deep Learning Signal Processing, Computer-Assisted Frontotemporal Dementia
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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...
Least-Squares Analysis Discriminant Analysis Fruit Algorithms Hyperspectral Imaging Pyrus Neural Networks, Computer Convolutional Neural Networks Calibration Principal Component Analysis 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...
Male Convolutional Neural Networks Creatinine Critical Care Neural Networks, Computer Humans Acute Kidney Injury Intensive Care Units
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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 ...
Cholelithiasis Diagnosis, Computer-Assisted Convolutional Neural Networks Ultrasonography Neural Networks, Computer Algorithms Humans
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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 ...
Neural Networks, Computer Animals Chromatography, High Pressure Liquid Tandem Mass Spectrometry Deep Learning Horses Convolutional Neural Networks Doping in Sports Discriminant Analysis
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