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 ...

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, ...

WASHINGTON, July 1, 2025 /PRNewswire/ — FinRegLab today released new empirical research demonstrating that adopting machine ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

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 ...