AIMC Topic: Neural Networks, Computer

Clear Filters Showing 3561 to 3570 of 31376 articles

WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in MR spectroscopic imaging.

Magnetic resonance in medicine
PURPOSE: Proton magnetic resonance spectroscopic imaging ( -MRSI) provides noninvasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain -MRSI are spectral overlap of metabolite peaks with large lipid signal fro...

A Novel State Space Model with Dynamic Graphic Neural Network for EEG Event Detection.

International journal of neural systems
Electroencephalography (EEG) is a widely used physiological signal to obtain information of brain activity, and its automatic detection holds significant research importance, which saves doctors' time, improves detection efficiency and accuracy. Howe...

Knee osteoarthritis severity detection using deep inception transfer learning.

Computers in biology and medicine
Osteoarthritis (OA) is a prevalent condition resulting in physical limitations. Early detection of OA is critical to effectively manage this condition. However, the diagnosis of early-stage arthritis remains challenging. The Kellgren and Lawrence (KL...

MEFA-Net: A mask enhanced feature aggregation network for polyp segmentation.

Computers in biology and medicine
Accurate polyp segmentation is crucial for early diagnosis and treatment of colorectal cancer. This is a challenging task for three main reasons: (i) the problem of model overfitting and weak generalization due to the multi-center distribution of dat...

Computerized classification method for significant coronary artery stenosis on whole-heart coronary MRA using 3D convolutional neural networks with attention mechanisms.

Radiological physics and technology
This study aims to develop a computerized classification method for significant coronary artery stenosis on whole-heart coronary magnetic resonance angiography (WHCMRA) images using a 3D convolutional neural network (3D-CNN) with attention mechanisms...

X-ray irradiation as a potential postharvest treatment for maintaining the quality of lily (Lilium davidii var. unicolor) bulbs and predicting shelf life using an artificial neural network.

Food research international (Ottawa, Ont.)
This study aimed to investigate the impact of X-ray irradiation pretreatment at varying doses (0.5, 1.0, 1.5, 2.0 kGy) on the preservation quality of lily bulbs and to elucidate its potential regulatory mechanisms. The findings revealed that X-ray ir...

An explainable machine learning system for efficient use of waste glasses in durable concrete to maximise carbon credits towards net zero emissions.

Waste management (New York, N.Y.)
Recycling waste glass (WG) can be time-consuming, costly, and impractical. However, its incorporation into concrete significantly reduces environmental impact and carbon emissions. This paper introduces machine learning (ML) to civil engineering to o...

Human intention recognition for trauma resuscitation: An interpretable deep learning approach for medical process data.

Journal of biomedical informatics
OBJECTIVE: Trauma resuscitation is the initial evaluation and management of injured patients in the emergency department. This time-critical process requires the simultaneous pursuit of multiple resuscitation goals. Recognizing whether the required g...

Optimizing Corn Tar Spot Measurement: A Deep Learning Approach Using Red-Green-Blue Imaging and the Stromata Contour Detection Algorithm for Leaf-Level Disease Severity Analysis.

Plant disease
Visual detection of stromata (brown-black, elevated fungal fruiting bodies) is the primary method for quantifying tar spot early in the season because these structures are definitive signs of the disease and essential for effective disease monitoring...

A computational deep learning investigation of animacy perception in the human brain.

Communications biology
The functional organization of the human object vision pathway distinguishes between animate and inanimate objects. To understand animacy perception, we explore the case of zoomorphic objects resembling animals. While the perception of these objects ...