ascopubs.org

A multivariate logistic regression model based on 3T mpMRI, clinical, and biopsy parameters for the prediction of prostate cancer extracapsular extension.

Impact of 68Ga-PSMA-11 PET/CT on staging and management of prostate cancer patients in various clinical settings. This is an ASCO Meeting Abstract from the 2020 Genitourinary Cancers Symposium. This ...
Investopedia

Multivariate Model: What it is, How it Works, Pros and Cons

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
JSTOR Daily

SELF-MODELING REGRESSION FOR MULTIVARIATE CURVE DATA

We present self-modeling regression models for flexible nonparametric modeling of multiple outcomes measured longitudinally. Based on penalized regression splines, the models borrow strength across ...
JSTOR Daily

Bayesian Regression with Multivariate Linear Splines

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 63, No. 1 (2001), pp. 3-17 (15 pages) We present a Bayesian analysis of a piecewise linear model constructed using ...
Healio

Multivariate model accurately predicted mortality risk in HF patients in the ED

Please provide your email address to receive an email when new articles are posted on . A model incorporating routinely collected variables accurately predicted 7-day mortality risk in HF patients ...
CU Boulder News & Events

Modeling space-time variability using multivariate semi-Bayesian hierarchical framework for seasonal total and extreme precipitation in the U.S. Northern Great Plains

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...
EurekAlert!

Illustrations of the Experimental Procedures of the Training Tasks (IMAGE)

A. Illustration of seven training tasks used in the experiment; B. average learning curves for each task; C. weights of contributed factors from the multivariate regression model; D. LASSO regression ...