AIMC Topic: Convolutional Neural Networks

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A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain-Computer Interfaces to Enhance Motor Imagery Classification.

Sensors (Basel, Switzerland) Jan 13, 2025
Enhancing motor disability assessment and its imagery classification is a significant concern in contemporary medical practice, necessitating reliable solutions to improve patient outcomes. One promising avenue is the use of brain-computer interfaces...
Brain Humans Brain-Computer Interfaces Convolutional Neural Networks Imagination Electroencephalography Neural Networks, Computer
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Genome-wide association study on color-image-based convolutional neural networks.

PeerJ Jan 13, 2025
BACKGROUND: Convolutional neural networks have excellent modeling abilities to complex large-scale datasets and have been applied to genomics. It requires converting genotype data to image format when employing convolutional neural networks to genome...
Genotype Color Genome-Wide Association Study Humans Image Processing, Computer-Assisted Neural Networks, Computer Convolutional Neural Networks
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Internal validation of a convolutional neural network pipeline for assessing meibomian gland structure from meibography.

Optometry and vision science : official publication of the American Academy of Optometry Jan 13, 2025
SIGNIFICANCE: Optimal meibography utilization and interpretation are hindered due to poor lid presentation, blurry images, or image artifacts and the challenges of applying clinical grading scales. These results, using the largest image dataset analy...
Meibomian Glands Meibomian Gland Dysfunction Neural Networks, Computer Algorithms Convolutional Neural Networks Diagnostic Techniques, Ophthalmological Reproducibility of Results Humans
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Bioinspired Smart Triboelectric Soft Pneumatic Actuator-Enabled Hand Rehabilitation Robot.

Advanced materials (Deerfield Beach, Fla.) Jan 10, 2025
Quantitative assessment for post-stroke spasticity remains a significant challenge due to the encountered variable resistance during passive stretching, which can lead to the widely used modified Ashworth scale (MAS) for spasticity assessment dependi...
Muscle Spasticity Nephropidae Stroke Stroke Rehabilitation Middle Aged Convolutional Neural Networks Male Equipment Design Hand Robotics Aged Adult Animals Humans Female
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Automatic medical imaging segmentation via self-supervising large-scale convolutional neural networks.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jan 9, 2025
PURPOSE: This study aims to develop a robust, large-scale deep learning model for medical image segmentation, leveraging self-supervised learning to overcome the limitations of supervised learning and data variability in clinical settings.
Neural Networks, Computer Tomography, X-Ray Computed Convolutional Neural Networks Image Processing, Computer-Assisted Deep Learning Humans
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Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models.

Sensors (Basel, Switzerland) Jan 7, 2025
Wheat is a globally cultivated cereal crop with substantial protein content present in its seeds. This research aimed to develop robust methods for predicting seed protein concentration in wheat seeds using bench-top hyperspectral imaging in the visi...
Support Vector Machine Seeds Triticum Convolutional Neural Networks Machine Learning Image Processing, Computer-Assisted Spectroscopy, Near-Infrared Hyperspectral Imaging Neural Networks, Computer Plant Proteins
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MFRC-Net: Multi-Scale Feature Residual Convolutional Neural Network for Motor Imagery Decoding.

IEEE journal of biomedical and health informatics Jan 7, 2025
Motor imagery (MI) decoding is the basis of external device control via electroencephalogram (EEG). However, the majority of studies prioritize enhancing the accuracy of decoding methods, often overlooking the magnitude and computational resource dem...
Imagination Neural Networks, Computer Convolutional Neural Networks Signal Processing, Computer-Assisted Electroencephalography Humans Brain-Computer Interfaces
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Melanoma Breslow Thickness Classification Using Ensemble-Based Knowledge Distillation With Semi-Supervised Convolutional Neural Networks.

IEEE journal of biomedical and health informatics Jan 7, 2025
Melanoma is considered a global public health challenge and is responsible for more than 90% deaths related to skin cancer. Although the diagnosis of early melanoma is the main goal of dermoscopy, the discrimination between dermoscopic images of in s...
Neural Networks, Computer Databases, Factual Melanoma Humans Convolutional Neural Networks Supervised Machine Learning Image Interpretation, Computer-Assisted Dermoscopy Skin Neoplasms Deep Learning
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Open-source Large Language Models can Generate Labels from Radiology Reports for Training Convolutional Neural Networks.

Academic radiology Jan 6, 2025
RATIONALE AND OBJECTIVES: Training Convolutional Neural Networks (CNN) requires large datasets with labeled data, which can be very labor-intensive to prepare. Radiology reports contain a lot of potentially useful information for such tasks. However,...
Humans Neural Networks, Computer Sensitivity and Specificity Ankle Fractures Large Language Models Convolutional Neural Networks Radiology Information Systems
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mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows.

International journal of biological macromolecules Jan 4, 2025
Glucose transporters are essential carrier proteins that function on the phospholipid bilayer to facilitate glucose diffusion across cell membranes. The transporters play many physiological and pathological roles in addition to absorption and metabol...
Humans Glucose Neural Networks, Computer Glucose Transport Proteins, Facilitative Convolutional Neural Networks
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