A tool for predicting Heart Disease probability based on ML model

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

Predicting Heart Disease using Machine Learning🫀🤖

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.

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

IotchulindraRai/Heart-disease-prediction-using-Ml-project with GUI

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

This is a Medical Prediction App which can be used to predict the current disease state of any human from any part of the world. This includes 3 main type of diseases - Covid-19, Diabetes, Heart Disease. Additionally it has a Medical Suggestions section which has some tips and guidelines for the ones affected by any of the disease

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

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

A heart disease prediction using deep learning

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

Identification system for the molecular basis of coronary heart disease powered by AI ( Artificial Intelligence ) and machine learning algorithms.

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

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

Heart Disease Prediction in Python