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 ...

Findings from a new study published in Annals of Family Medicine show that a machine learning model accurately predicts ...

A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.

The groups that correspond to carbon, nitrogen, and oxygen were best -- or group numbers 14, 15, and 16, respectively. Logistic regression is a statistical method that can tell apart two objects.

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, ...

A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, according to research published in Gastroenterology.The model, which used Random ...

We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of ...