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Researchers investigate COVID-19 data with logistic regression model training
As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data ... the logistic regression model, 3,386 samples were used for the analysis ...
technologynetworks2mon
Logistic Regression
Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
The American Journal of Managed Care1d
Cost vs Accuracy: Choosing the Best ML Model for Vascular Calcification in CKD
While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...
Simon Fraser University8y
Example 39.9: Conditional Logistic Regression for Matched Pairs Data
In matched case-control studies, conditional logistic regression is used ... are 63 observations in the data set, one for each matched pair. The variable Outcome has a constant value of 0. proc ...
Lasso-LR model best for predicting AKI mortality in alcoholic cirrhosis
The least absolute shrinkage and selection operator-logistic regression (Lasso-LR) model is optimal for predicting ...
Harvard Business Review9y
A Refresher on Regression Analysis
Understanding one of the most important types of data analysis. by Amy Gallo You probably know by now that whenever possible you should be making data-driven decisions at work. But do you know how ...
ascopubs.org19y
Logistic Regression Model to Distinguish Between the Benign and Malignant Adnexal Mass Before Surgery: A Multicenter Study by the International Ovarian Tumor Analysis Group
Multicenter Phase I/II Study of Cetuximab With Paclitaxel and Carboplatin in Untreated Patients With Stage IV Non–Small-Cell Lung Cancer Data from 1,066 patients recruited from nine European centers ...