Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, ...

This is closely related to the traditional statistical application of the method, the key difference being that in machine learning, logistic regression is used to develop a model that learns from ...

There has been much recent interest in use of machine learning (ML) for cancer prediction, but few studies comparing ML with classical statistical models for NCGC risk prediction. Methods We trained ...

EHR data may be particularly suitable for machine learning (ML) techniques, as such algorithms can process high-dimensional data and capture nonlinear relationships between variables. By comparison, ...