AIMC Topic: Neural Networks, Computer

Clear Filters Showing 21991 to 22000 of 31376 articles

Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

European radiology
OBJECTIVES: The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated constru...

Novel machine learning application for prediction of membrane insertion potential of cell-penetrating peptides.

International journal of pharmaceutics
Cell-penetrating peptides (CPPs) are often used as transporter systems to deliver various therapeutic agents into the cell. We developed a novel machine learning application which can quantitatively screen the insertion/interaction potential of vario...

A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats.

Sensors (Basel, Switzerland)
Mosquito control is important as mosquitoes are extremely harmful pests that spread various infectious diseases. In this research, we present the preliminary results of an automated system that detects the presence of mosquitoes via image processing ...

Learning cellular morphology with neural networks.

Nature communications
Reconstruction and annotation of volume electron microscopy data sets of brain tissue is challenging but can reveal invaluable information about neuronal circuits. Significant progress has recently been made in automated neuron reconstruction as well...

Artificial neural network models to predict nodal status in clinically node-negative breast cancer.

BMC cancer
BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard staging procedure for nodal status in breast cancer, but lacks therapeutic benefit for patients with benign sentinel nodes. For patients with positive sentinel nodes, individualized surgical s...

Completely Automated CNN Architecture Design Based on Blocks.

IEEE transactions on neural networks and learning systems
The performance of convolutional neural networks (CNNs) highly relies on their architectures. In order to design a CNN with promising performance, extensive expertise in both CNNs and the investigated problem domain is required, which is not necessar...

Role of deep learning in infant brain MRI analysis.

Magnetic resonance imaging
Deep learning algorithms and in particular convolutional networks have shown tremendous success in medical image analysis applications, though relatively few methods have been applied to infant MRI data due numerous inherent challenges such as inhomo...

Deep learning assisted mitotic counting for breast cancer.

Laboratory investigation; a journal of technical methods and pathology
As part of routine histological grading, for every invasive breast cancer the mitotic count is assessed by counting mitoses in the (visually selected) region with the highest proliferative activity. Because this procedure is prone to subjectivity, th...

Deep Learning Preoperatively Predicts Value Metrics for Primary Total Knee Arthroplasty: Development and Validation of an Artificial Neural Network Model.

The Journal of arthroplasty
BACKGROUND: The objective is to develop and validate an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition before primary total knee arthroplasty (TKA). The secondary objective ...

Biologically plausible deep learning - But how far can we go with shallow networks?

Neural networks : the official journal of the International Neural Network Society
Training deep neural networks with the error backpropagation algorithm is considered implausible from a biological perspective. Numerous recent publications suggest elaborate models for biologically plausible variants of deep learning, typically defi...