Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

TRAIL Score: A Simple Model to Predict Immunochemotherapy Tolerability in Patients With Diffuse Large B-Cell Lymphoma We trained models using logistic regression (LR) and four commonly used ML ...

Logistic regression has found wide acceptance as a model for the dependence of a binary response variable on a vector of explanatory variables. It can also be used, however, as a maximization ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...