Modern healthcare is getting reshaped by growing Electronic Medical Records (EMR). Recently, these records have been shown of great value towards building clinical prediction models. In EMR data, patients' diseases and hospital interventions are capt...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Dec 8, 2014
This study describes a simple and rapid approach of monitoring celecoxib (CLX). Unfolded principal component analysis-radial basis function neural network (UPCA-RBFNN) and excitation-emission spectra were combined to develop new model in the determin...
BACKGROUND: Robot-assisted laparoscopic radical prostatectomy has become a widespread technique despite a lack of randomised trials showing its superiority over open radical prostatectomy.
Primers plays important role in polymerase chain reaction (PCR) experiments, thus it is necessary to select characteristic primers. Unfortunately, manual primer design manners are time-consuming and easy to get human negligence because many PCR const...
IEEE transactions on neural networks and learning systems
Jul 23, 2014
This brief considers the guaranteed H∞ performance state estimation problem of delayed static neural networks. An Arcak-type state estimator, which is more general than the widely adopted Luenberger-type one, is chosen to tackle this issue. A delay-d...
International journal of computer assisted radiology and surgery
May 16, 2014
PURPOSE: Robotic radiotherapy can precisely ablate moving tumors when time latencies have been compensated. Recently, relevance vector machines (RVM), a probabilistic regression technique, outperformed six other prediction algorithms for respiratory ...
Nitrogen-fixing microorganisms play a critical role in the global nitrogen cycle by converting atmospheric nitrogen into ammonia through the action of nitrogenase (EC 1.18.6.1). In this study, we employed six machine learning algorithms to model the ...
Random forest (RF) regression is popular machine learning method to develop prediction models for continuous outcomes. Variable selection, also known as feature selection or reduction, involves selecting a subset of predictor variables for modeling. ...
Dry matter intake (DMI) is a measure critical to managing and evaluating livestock. Methods exist for quantifying individual DMI in dry lot settings that employ expensive intake systems. No methods exist to accurately measure individual DMI of grazin...