AIMC Topic: Neural Networks, Computer

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Artificial neural networks to predict 3D spinal posture in reaching and lifting activities; Applications in biomechanical models.

Journal of biomechanics
Spinal posture is a crucial input in biomechanical models and an essential factor in ergonomics investigations to evaluate risk of low back injury. In vivo measurement of spinal posture through the common motion capture techniques is limited to equip...

The evaluation of i-SIDRA - a tool for intelligent feedback - in a course on the anatomy of the locomotor system.

International journal of medical informatics
OBJECTIVE: This paper presents an empirical study of a formative mobile-based assessment approach that can be used to provide students with intelligent diagnostic feedback to test its educational effectiveness.

Boundedness and convergence analysis of weight elimination for cyclic training of neural networks.

Neural networks : the official journal of the International Neural Network Society
Weight elimination offers a simple and efficient improvement of training algorithm of feedforward neural networks. It is a general regularization technique in terms of the flexible scaling parameters. Actually, the weight elimination technique also c...

Event-triggered H∞ filter design for delayed neural network with quantization.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with H∞ filter design for a class of neural network systems with event-triggered communication scheme and quantization. Firstly, a new event-triggered communication scheme is introduced to determine whether or not the current ...

Artificial Neural Network for Total Laboratory Automation to Improve the Management of Sample Dilution.

SLAS technology
Diluting a sample to obtain a measure within the analytical range is a common task in clinical laboratories. However, for urgent samples, it can cause delays in test reporting, which can put patients' safety at risk. The aim of this work is to show a...

Basal Ganglia dysfunctions in movement disorders: What can be learned from computational simulations.

Movement disorders : official journal of the Movement Disorder Society
The basal ganglia are a complex neuronal system that is impaired in several movement disorders, including Parkinson's disease, Huntington's disease, and dystonia. Empirical studies have provided valuable insights into the brain dysfunctions underlyin...

A new thresholding technique based on fuzzy set as an application to leukocyte nucleus segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The main aim of this paper is to segment leukocytes in blood smear images using interval-valued intuitionistic fuzzy sets (IVIFSs). Generally, uncertainties occur in terms of vagueness through brightness levels of image. Pr...

Complex Neural Network Models for Time-Varying Drazin Inverse.

Neural computation
Two complex Zhang neural network (ZNN) models for computing the Drazin inverse of arbitrary time-varying complex square matrix are presented. The design of these neural networks is based on corresponding matrix-valued error functions arising from the...

Pan-Specific Prediction of Peptide-MHC Class I Complex Stability, a Correlate of T Cell Immunogenicity.

Journal of immunology (Baltimore, Md. : 1950)
Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. ...

Confirming an integrated pathology of diabetes and its complications by molecular biomarker-target network analysis.

Molecular medicine reports
Despite ongoing research into diabetes and its complications, the underlying molecular associations remain to be elucidated. The systematic identification of molecular interactions in associated diseases may be approached using a network analysis str...