Model includes age, body mass index, hypertriglyceridemia, tumor staging, tumor grade, CA125 level, platelet count, fibrinogen level.

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

The R package rcssci offers an intuitive solution for visualizing Restricted Cubic Splines (RCS) in regression analyses. It automates the generation of spline plots for outcomes like odds ratios (OR), ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

Introduction In the USA, most tobacco control research has focused on federal-level and state-level policies. However, ...

Background Current guidelines for aortic valve replacement (AVR) lack consensus on prosthesis selection in middle-aged patients. This study aimed to provide a comprehensive comparison of long-term ...

The categorical outcomes were analysed using logistic regression models, with treatment allocation as an independent ... the support of the Northern Ireland Clinical Trials Unit. AI use statement: ...

The Model Context Protocol (MCP) provides a modern, semantically rich way for AI to interact with enterprise systems.

The European Commission set out guidelines on Friday to help AI models it has determined have systemic risks and face tougher ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...