AIMC Topic: Linear Models

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Prediction of stenosis behaviour in artery by neural network and multiple linear regressions.

Biomechanics and modeling in mechanobiology
Blood flow analysis in the artery is a paramount study in the field of arterial stenosis evaluation. Studies conducted so far have reported the analysis of blood flow parameters using different techniques, but the regression analysis is not adequatel...

Dynamics of unidirectionally-coupled ring neural network with discrete and distributed delays.

Journal of mathematical biology
In this paper, we consider a ring neural network with one-way distributed-delay coupling between the neurons and a discrete delayed self-feedback. In the general case of the distribution kernels, we are able to find a subset of the amplitude death re...

Application of artificial neural network and multiple linear regression in modeling nutrient recovery in vermicompost under different conditions.

Bioresource technology
Vermicomposting is one of the best technologies for nutrient recovery from solid waste. This study aims to assess the efficiency of Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) models in predicting nutrient recovery from solid...

A reliable time-series method for predicting arthritic disease outcomes: New step from regression toward a nonlinear artificial intelligence method.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The interrupted time-series (ITS) concept is performed using linear regression to evaluate the impact of policy changes in public health at a specific time. Objectives of this study were to verify, with an artificial intelli...

Predicting the serum digoxin concentrations of infants in the neonatal intensive care unit through an artificial neural network.

BMC pediatrics
BACKGROUND: Given its narrow therapeutic range, digoxin's pharmacokinetic parameters in infants are difficult to predict due to variation in birth weight and gestational age, especially for critically ill newborns. There is limited evidence to suppor...

Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction.

Scientific data
The immune response to major trauma has been analysed mainly within post-hospital admission settings where the inflammatory response is already underway and the early drivers of clinical outcome cannot be readily determined. Thus, there is a need to ...

Estimate ecotoxicity characterization factors for chemicals in life cycle assessment using machine learning models.

Environment international
In life cycle assessment, characterization factors are used to convert the amount of the chemicals and other pollutants generated in a product's life cycle to the standard unit of an impact category, such as ecotoxicity. However, as a widely used imp...

Particle Swarm Optimized Hybrid Kernel-Based Multiclass Support Vector Machine for Microarray Cancer Data Analysis.

BioMed research international
Determining an optimal decision model is an important but difficult combinatorial task in imbalanced microarray-based cancer classification. Though the multiclass support vector machine (MCSVM) has already made an important contribution in this field...

Fuzzy jump wavelet neural network based on rule induction for dynamic nonlinear system identification with real data applications.

PloS one
AIM: Fuzzy wavelet neural network (FWNN) has proven to be a promising strategy in the identification of nonlinear systems. The network considers both global and local properties, deals with imprecision present in sensory data, leading to desired prec...