AIMC Topic: Deep Learning

Clear Filters Showing 4271 to 4280 of 28423 articles

Identifying the presence of atrial fibrillation during sinus rhythm using a dual-input mixed neural network with ECG coloring technology.

BMC medical research methodology
BACKGROUND: Undetected atrial fibrillation (AF) poses a significant risk of stroke and cardiovascular mortality. However, diagnosing AF in real-time can be challenging as the arrhythmia is often not captured instantly. To address this issue, a deep-l...

Improved enzyme functional annotation prediction using contrastive learning with structural inference.

Communications biology
Recent years have witnessed the remarkable progress of deep learning within the realm of scientific disciplines, yielding a wealth of promising outcomes. A prominent challenge within this domain has been the task of predicting enzyme function, a comp...

Machine Learning and Deep Learning for Diagnosis of Lumbar Spinal Stenosis: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Lumbar spinal stenosis (LSS) is a major cause of pain and disability in older individuals worldwide. Although increasing studies of traditional machine learning (TML) and deep learning (DL) were conducted in the field of diagnosing LSS an...

Fast motion-compensated reconstruction for 4D-CBCT using deep learning-based groupwise registration.

Biomedical physics & engineering express
. Previous work has that deep learning (DL)-enhanced 4D cone beam computed tomography (4D-CBCT) images improve motion modeling and subsequent motion-compensated (MoCo) reconstruction for 4D-CBCT. However, building the motion model at treatment time v...

Other possible perspectives for solving the negative outcome penalty paradox in the application of artificial intelligence in clinical diagnostics.

Journal of medical ethics
Artificial intelligence (AI), represented by machine learning, artificial neural networks and deep learning, is impacting all areas of medicine, including translational research (from bench to bedside to health policy), clinical medicine (including d...

Automatic identification of the endangered hawksbill sea turtle behavior using deep learning and cross-species transfer learning.

The Journal of experimental biology
The accelerometer, an onboard sensor, enables remote monitoring of animal posture and movement, allowing researchers to deduce behaviors. Despite the automated analysis capabilities provided by deep learning, data scarcity remains a challenge in ecol...

Detection and location of EEG events using deep learning visual inspection.

PloS one
The electroencephalogram (EEG) is a major diagnostic tool that provides detailed insight into the electrical activity of the brain. This signal contains a number of distinctive waveform patterns that reflect the subject's health state in relation to ...

Lightweight deep learning algorithm for real-time wheat flour quality detection via NIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat flour quality, determined by factors such as protein and moisture content, is crucial in food production. Traditional methods for analyzing these parameters, though precise, are time-consuming and impractical for large-scale operations. This st...

Tea grading, blending, and matching based on computer vision and deep learning.

Journal of the science of food and agriculture
BACKGROUND: Accurate tea blending assessment and sample matching are critical in the tea production process. Traditional methods face efficiency and accuracy challenges, which can be addressed by advances in computer vision and deep learning. This st...