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Least-Squares Analysis

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Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD.

Magnetic resonance in medicine
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...

Detection of Moving Object in Dynamic Visual Sequences Based on Partial Least Squares Classifier.

Journal of medical systems
Detection of moving object from a visual sequence plays a vital role for the tracking of object. The main objective of this proposed work is to detect and classify the various video sequences with the help of different classification algorithms. The ...

Application of artificial neural networks for Process Analytical Technology-based dissolution testing.

International journal of pharmaceutics
This work proposes the application of artificial neural networks (ANN) to non-destructively predict the in vitro dissolution of pharmaceutical tablets from Process Analytical Technology (PAT) data. An extended release tablet formulation was studied, ...

Functional form estimation using oblique projection matrices for LS-SVM regression models.

PloS one
Kernel regression models have been used as non-parametric methods for fitting experimental data. However, due to their non-parametric nature, they belong to the so-called "black box" models, indicating that the relation between the input variables an...

Online sequential echo state network with sparse RLS algorithm for time series prediction.

Neural networks : the official journal of the International Neural Network Society
Recently, the echo state networks (ESNs) have been widely used for time series prediction. To meet the demand of actual applications and avoid the overfitting issue, the online sequential ESN with sparse recursive least squares (OSESN-SRLS) algorithm...

Soft-sensing method based on FDLS-SVM in marine alkaline protease fermentation process.

Preparative biochemistry & biotechnology
To overcome the problem that soft-sensing model cannot be updated with the bioprocess changes, this article proposed a soft-sensing modeling method which combined fuzzy c-means clustering (FCM) algorithm with least squares support vector machine theo...

High-Sensitivity Determination of Nutrient Elements in by Laser-induced Breakdown Spectroscopy and Chemometric Methods.

Molecules (Basel, Switzerland)
High-accuracy and fast detection of nutritive elements in traditional Chinese medicine (PN) is beneficial for providing useful assessment of the healthy alimentation and pharmaceutical value of PN herbs. Laser-induced breakdown spectroscopy (LIBS) w...

A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.

Medical physics
PURPOSE: This work aims to develop a new framework of image quality assessment using deep learning-based model observer (DL-MO) and to validate it in a low-contrast lesion detection task that involves CT images with patient anatomical background.

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

Journal of affective disorders
BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to one type of disease. Unveiling the association between depressive and the fatigue diseases provides a...

Using artificial neural network and multivariate calibration methods for simultaneous spectrophotometric analysis of Emtricitabine and Tenofovir alafenamide fumarate in pharmaceutical formulation of HIV drug.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Spectrophotometric analysis method based on artificial neural network (ANN), partial least squares regression (PLS) and principal component regression (PCR) models was proposed for the simultaneous determination of Emtricitabine (ETB) and Tenofovir a...