Build a Web App called AI-Powered Heart Disease Risk Assessment App

This Experiment provides a comprehensive approach to forecast heart disease risks by performing a detailed data analysis, predictive modeling & hyperparameter tuning. This leads to a `LinearSVC` model with 90% Accuracy

It is a medical chatbot that will provide quick answers to FAQs by setting up rule-based keyword chatbots.

Heart disease prediction project for CMC-16 (Data Science Practices) course.

Streamlit web app to early predict heart attack

EDA, visualizations and model training were done over the Heart Disease Dataset. Web app was made using HTML, CSS and Flask, which allows user to enter their medical info and check the risk of heart disease. A KNN model was deployed into the web-app using Python's Pickle module to make the risk prediction based on medical into entered by user.

Artificial intelligence in medical science plays a vital role and That's why I build this Model to predict Hert Disese.

Heart Disease Prediction by Python

This project aims to predict the presence of heart disease based on various medical attributes of an individual. It utilizes a logistic regression model trained on a dataset containing information about patients and whether they have heart disease or not.

A Machine Learning project for Cardiovascular disease prediction

Analyze the heart disease dataset to explore the machine learning algorithms and build multiple models and find best performing one to predict the disease.

Deployed medical apps on streamlit

You are tasked to perform Heart Disease Prediction Using Logistic Regression. The World Health Organization has estimated that four out of five cardiovascular disease (CVD) deaths are due to heart attacks. This whole research intends to pinpoint the ratio of patients who have a good chance of being affected by CVD and predict the overall risk using

A machine learning web application use to predict chances of heart disease, built with FLASK and deployed on Heroku.

This one is advance version of the earlier one i.e Multiple disease prediction as we can run it just by cloning vs GitHub desktop and run it in vscode

this repository is part of multiple disease prediction system repository

This a multiple disease prediction based on user input which can predict upto 40 disease and trained on 131 parameters

this is combination of 3 different disease prediction system check readme for details

This repository contains the implementation of a Convolutional Neural Network (CNN) model for the classification of heart sound signals into five categories using short-term Fourier transform (STFT) features.

A group project on cardiovascular disease prediction