framingham

This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project

HACSurv: A Hierarchical Copula-based Approach for Survival Analysis with Dependent Competing Risks

A web app for beginners in Machine Learning and Data Science to fiddle with different parameters of various ML algorithms on the Framingham Heart Disease dataset.

r-framingham is a package used to estimate the 10-year cardiovascular risk of an individual using Framingham_Risk_Score standard guidelines

Framingham data progressive unidirectional multi-state model using four states: No disease, Hypertension, Cardiovascular disease, and Death (absorbing).

AI-powered web app for early detection of 10-year Coronary Heart Disease risk using an ensemble of XGBoost, LightGBM & CatBoost trained on the Framingham Heart Study dataset.

Unofficial repository with some useful Framingham city data, including local election results and precinct shapefiles.

An implementation of the Framingham CVD risk score with DMN

The SVM-based Heart Disease Prediction code is a Python implementation that utilizes Support Vector Machines (SVM) to predict the risk of cardiovascular disease. The code works with the Framingham Heart Study dataset, which contains demographic, behavioral, and medical risk factors of individuals.

Heart Disease Prediction using Machine Learning with the Framingham Heart Study Dataset.

R statistical modeling projects including Framingham & Digitalis models

Rifaz AI — AI-powered cardiovascular risk analysis (BP tracking, heart-risk prediction, Framingham scoring). By Safe Tech Solutions.