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 ...

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, ...

Machine learning revolves around several core algorithmic frameworks to achieve results and produce models that are useful, including neural networks, linear and logistic regression, clustering ...

Methods 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 ...