The goal of this project is to develop and evaluate machine learning models that predict heart disease in individuals based on the available features.

This project develops a machine learning model to predict heart disease risk based on symptoms and medical history. The model achieved the best accuracy with Logistic Regression, as it works well for binary classification problems.

The Heart Disease Prediction Model uses Logistic Regression to predict heart disease risk from user-inputted medical data through a Flask web app. Users enter details like age and blood pressure to get predictions, with model persistence handled by pickle. Future enhancements include UI improvements and additional machine learning models.

CorVita, derived from the Latin words "Cor" for "Heart" and "Vita" for "Life", is a comprehensive heart health application.

Heart Disease Prediction using Logistic Regression: A Machine Learning Approach for Predictive Analytics in Healthcare.

Heart Disease Prediction in Python

Agent Based Software Engineering Semester Project in python: Heart Disease Prediction . Complete User Interface along MYSQL database connection to store data .

we predict that the patient is suffering with heart attack or not

This repository presents a machine learning project aimed at building a predictive model for heart disease. To improve the model's ability to classify patients who are borderline cases, we employ Synthetic Minority Over-sampling Technique (SMOTE).

Heart Disease Prediction with FastAPI

Machine Learning for Heart Disease prediction

A heart disease prediction using deep learning

Project to predict heart diseases

Analysed the performance of different Machine Learning algorithms on Coronary heart disease dataset acquired from Kaggle. Performed EDA, Data cleansing, data pre processing and feature correlation, feature selection. Implemented Logistic regression with 10 fold cross validation, Logistic regression with GridSearchCV, Random Forest, RNN and MLP

Health related machine learning projects

heart disease prediction model in which you can predict if a person is healthy or having a heart disease

Predicting Heart Disease using Machine Learning🫀🤖

Heart Disease Analysis to explore, diagnose and highlight potential factors to predict the disease chance in future.

This is a machine learning project that uses various machine learning alogorithms to predict whether a patient is suffering from heart disease or not. Here I am using variour machine learning algorithms like Random Forest classifier, XGBClassifier, GaussianNB, Decision Tree Classifier, K-Nearest Neighbours and Logistic Regression.

Statistical analysis in R of a heart disease dataset by using logistic regression and random forest.