AIMC Topic: Neural Networks, Computer

Clear Filters Showing 19241 to 19250 of 31376 articles

Generalized Deep Neural Network Model for Cuffless Blood Pressure Estimation with Photoplethysmogram Signal Only.

Sensors (Basel, Switzerland)
Due to the growing public awareness of cardiovascular disease (CVD), blood pressure (BP) estimation models have been developed based on physiological parameters extracted from both electrocardiograms (ECGs) and photoplethysmograms (PPGs). Still, in o...

Estimating 3-dimensional liver motion using deep learning and 2-dimensional ultrasound images.

International journal of computer assisted radiology and surgery
PURPOSE: The main purpose of this study is to construct a system to track the tumor position during radiofrequency ablation (RFA) treatment. Existing tumor tracking systems are designed to track a tumor in a two-dimensional (2D) ultrasound (US) image...

Technical Note: Automatic segmentation of CT images for ventral body composition analysis.

Medical physics
PURPOSE: Body composition is known to be associated with many diseases including diabetes, cancers, and cardiovascular diseases. In this paper, we developed a fully automatic body tissue decomposition procedure to segment three major compartments tha...

Detecting myocardial scar using electrocardiogram data and deep neural networks.

Biological chemistry
Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischae...

Deep neural network improves the estimation of polygenic risk scores for breast cancer.

Journal of human genetics
Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. In this study, we compared a series of computational models for estimation of breast cancer PRS. A de...

Robust parallel decision-making in neural circuits with nonlinear inhibition.

Proceedings of the National Academy of Sciences of the United States of America
An elemental computation in the brain is to identify the best in a set of options and report its value. It is required for inference, decision-making, optimization, action selection, consensus, and foraging. Neural computing is considered powerful be...

Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision.

PLoS computational biology
Deep feedforward neural network models of vision dominate in both computational neuroscience and engineering. The primate visual system, by contrast, contains abundant recurrent connections. Recurrent signal flow enables recycling of limited computat...

Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks.

European radiology
OBJECTIVE: To explore the application of deep learning in patients with primary osteoporosis, and to develop a fully automatic method based on deep convolutional neural network (DCNN) for vertebral body segmentation and bone mineral density (BMD) cal...