AIMC Topic: Neural Networks, Computer

Clear Filters Showing 20141 to 20150 of 31376 articles

Development of a real-time indoor location system using bluetooth low energy technology and deep learning to facilitate clinical applications.

Medical physics
PURPOSE: An indoor, real-time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data-driven optimization of procedures. Bluetooth-based RTLS systems are cost-effective but lack accuracy because Bl...

DeepDistance: A multi-task deep regression model for cell detection in inverted microscopy images.

Medical image analysis
This paper presents a new deep regression model, which we call DeepDistance, for cell detection in images acquired with inverted microscopy. This model considers cell detection as a task of finding most probable locations that suggest cell centers in...

Binding Affinity Prediction by Pairwise Function Based on Neural Network.

Journal of chemical information and modeling
We present a new approach to estimate the binding affinity from given three-dimensional poses of protein-ligand complexes. In this scheme, every protein-ligand atom pair makes an additive free-energy contribution. The sum of these pairwise contributi...

Proposing a convolutional neural network for stress assessment by means of derived heart rate from functional near infrared spectroscopy.

Computers in biology and medicine
BACKGROUND: Stress is known as one of the major factors threatening human health. A large number of studies have been performed in order to either assess or relieve stress by analyzing the brain and heart-related signals.

An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases.

Interdisciplinary sciences, computational life sciences
Malaria is one of the epidemics that can cause human death. Accurate and rapid diagnosis of malaria is important for treatment. Due to the limited number of data and human factors, the prediction performance and reliability of traditional classificat...

Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network.

Nature medicine
The electrocardiogram (ECG) is a widely used medical test, consisting of voltage versus time traces collected from surface recordings over the heart. Here we hypothesized that a deep neural network (DNN) can predict an important future clinical event...

Estimation of glandular dose in mammography based on artificial neural networks.

Physics in medicine and biology
This work proposes using artificial neural networks (ANNs) for the regression of the dosimetric quantities employed in mammography. The data were generated by Monte Carlo (MC) simulations using a modified and validated version of the PENELOPE (v. 201...

Detection of Atrial Fibrillation from Single Lead ECG Signal Using Multirate Cosine Filter Bank and Deep Neural Network.

Journal of medical systems
Atrial fibrillation (AF) is a cardiac arrhythmia which is characterized based on the irregsular beating of atria, resulting in, the abnormal atrial patterns that are observed in the electrocardiogram (ECG) signal. The early detection of this patholog...

Contextual encoder-decoder network for visual saliency prediction.

Neural networks : the official journal of the International Neural Network Society
Predicting salient regions in natural images requires the detection of objects that are present in a scene. To develop robust representations for this challenging task, high-level visual features at multiple spatial scales must be extracted and augme...

Simplification of neural networks for skin lesion image segmentation using color channel pruning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automatic analysis of skin abnormality is an effective way for medical experts to facilitate diagnosis procedures and improve their capabilities. Efficient and accurate methods for analysis of the skin abnormalities such as convolutional neural netwo...