Quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (FA-MLR), principle component regression analysis (PCRA), and genetic algorithm-partial least squares GA-PLS. The FA-MLR describes the effect of geometrical and quantum indices on enzyme inhibition act...

This study introduces the use of multivariate linear regression (MLR) and support vector regression (SVR) models to predict postoperative outcomes in a cohort of patients who underwent surgery for cervical spondylotic myelopathy (CSM). Currently, predicting outcomes after surgery for CSM remains a challenge. We recruited patients who had a diagnosis of CSM and required decompressive surgery wit...

We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). This was verified in 25 healthy subjects, aged 28 ± 5 years. The multiple linear regression (MLR) and support vector regression (SVR) models were used to examine the...

EMPs Extended morphological profiles EMPs Extended morphological profiles LDA Linear discriminant analysis LogDA Logarithmic discriminant analysis MLR Multinomial logistic regression MLRsubMRF Subspace-based multinomial logistic regression followed by Markov random fields MPs Morphological profiles MRFs Markov random fields PCA Principal component analysis QDA Quadratic discriminant analysis RH...

a reliable quantitative structure retention relationship (qsrr) study has been evaluated to predict the retention indices (ris) of a broad spectrum of compounds, namely 118 non-linear, cyclic and heterocyclic terpenoids (both saturated and unsaturated), on an hp-5ms fused silica column. a principal component analysis showed that seven compounds lay outside of the main cluster. after elimination...

The present work describes a comparison of the ability of multiple linear regression (MLR) and artificial neural networks (ANN) to predict fish spatial occupancy and abundance in a mesotrophic reservoir. Models were run and tested with 306 observations obtained by the sampling point abundance method using electrofishing. For each of the 306 samples, the relationships between physical parameters...

BACKGROUND Epidemiological evidence suggests that vitamin D deficiency is linked to various chronic diseases. However direct measurement of serum 25-hydroxyvitamin D (25(OH)D) concentration, the accepted biomarker of vitamin D status, may not be feasible in large epidemiological studies. An alternative approach is to estimate vitamin D status using a predictive model based on parameters derived...

Ground-level ozone (O3) is one of the most significant forms air pollution around world due to its ability cause adverse effects on human health and environment. Understanding variation association O3 level with precursors weather parameters important for developing precise forecasting models that are needed mitigation planning early warning purposes. In this study, hourly data (O3, CO, NO2, PM...

The standard enthalpy of formation of 1115 compounds from all chemical groups, were predicted using genetic algorithm-based multivariate linear regression (GAMLR). The obtained multivariate linear five descriptors model by GA-MLR has correlation coefficient ( 9830 . 0 2 = R ). All molecular descriptors which have entered in this model are calculated from chemical structure of any molecule. As a...