AIMC Topic: Neural Networks, Computer

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T-wave end detection using neural networks and Support Vector Machines.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: In this paper we propose a new approach for detecting the end of the T-wave in the electrocardiogram (ECG) using Neural Networks and Support Vector Machines.

Convolution neural networks for real-time needle detection and localization in 2D ultrasound.

International journal of computer assisted radiology and surgery
PURPOSE: We propose a framework for automatic and accurate detection of steeply inserted needles in 2D ultrasound data using convolution neural networks. We demonstrate its application in needle trajectory estimation and tip localization.

Deep Learning and Its Applications in Biomedicine.

Genomics, proteomics & bioinformatics
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the und...

3D Molecular Representations Based on the Wave Transform for Convolutional Neural Networks.

Molecular pharmaceutics
Convolutional neural networks (CNN) have been successfully used to handle three-dimensional data and are a natural match for data with spatial structure such as 3D molecular structures. However, a direct 3D representation of a molecule with atoms loc...

Using deep learning to model the hierarchical structure and function of a cell.

Nature methods
Although artificial neural networks are powerful classifiers, their internal structures are hard to interpret. In the life sciences, extensive knowledge of cell biology provides an opportunity to design visible neural networks (VNNs) that couple the ...

Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

Scientific reports
The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the popul...

Deep Spatial-Temporal Joint Feature Representation for Video Object Detection.

Sensors (Basel, Switzerland)
With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detec...

Feasibility of an AI-Based Measure of the Hand Motions of Expert and Novice Surgeons.

Computational and mathematical methods in medicine
This study investigated whether parameters derived from hand motions of expert and novice surgeons accurately and objectively reflect laparoscopic surgical skill levels using an artificial intelligence system consisting of a three-layer chaos neural ...

Tissue classification and segmentation of pressure injuries using convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: This paper presents a new approach for automatic tissue classification in pressure injuries. These wounds are localized skin damages which need frequent diagnosis and treatment. Therefore, a reliable and accurate systems fo...

Classifying dynamic transitions in high dimensional neural mass models: A random forest approach.

PLoS computational biology
Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understan...