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

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

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

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

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.

R statistical modeling projects including Framingham & Digitalis models

This project contains a Python implementation of logistic regression to predict the risk of developing heart disease in the next 10 years, based on the Framingham dataset from Kaggle. The implementation achieved an accuracy of 87.27% on the test set. The code is available on GitHub under the repository name "HeartDiseaseRiskLR".