R code for the data managment and statistical analysis performed for Association with and outcomes after non-cardiology vs. cardiology care in heart failure: Observations from SwedeHF

Evaluation of electrophysiological signals

Predicting First-Year Survival after Percutaneous Coronary Interventions: A Machine Learning-Based ShinyApp Web Application in R

CTAMACE is a web application which can be used to predict major cardiovascular events (MACE) two years following coronary multidetector computed tomography (MDCT) using combined anatomical coronary findings and clinical features

CardioSTAT is an advanced R-based framework for heart disease classification and prediction, integrating statistical and machine learning approaches. This hybrid model combines ordinal regression with XGBoost for accurate classification and severity prediction, while offering extensive ROC analysis, statistical testing, and visualization tools.