The Heart Disease Prediction project is dedicated to utilizing machine learning models to predict the likelihood of heart disease. This repository contains a collection of files, datasets, and machine learning models tailored for heart disease prediction. These resources aim to facilitate early detection and risk assessment of heart disease, enabling individuals to make informed health decisions.
- Heart disease completed.py (working main model): This file contains the primary code for the heart disease prediction model.
- Heart disease prediction with pictoblox.sb3: A version of the heart disease prediction model implemented in PictoBlox, a visual programming language.
- Heart disease prediction with spyder.py (same as google collab file but just a Spyder version): A Spyder version of the code for heart disease prediction.
- Heart_Disease_Prediction.csv: A dataset used for improving prediction scores.
- heart.csv: A dataset used for heart disease prediction.
- heart_disease_data.csv: Another dataset used in the project.
- heart_disease_prediction.py (Google Colab file): A Google Colab version of the heart disease prediction model.
- Utilizes three different CSV datasets to improve prediction scores.
- Trained on a logistic regression model.
- Provides a PictoBlox version for educational purposes and ease of understanding.
To use the Heart Disease Prediction project, follow these steps:
- Choose the appropriate file for your needs: "Heart disease completed.py," "Heart disease prediction with spyder.py," or "heart_disease_prediction.py."
- Ensure that you have the required datasets: "Heart_Disease_Prediction.csv," "heart.csv," and "heart_disease_data.csv."
- Run the code to predict heart disease based on the provided dataset.
If you encounter any issues or have questions, please don't hesitate to reach out for support.
Happy predicting! 🤖💙
Check out the main repo as this project is part of it
Sudhanshu Ambastha |
Parth Shrivastava |
Sarthak Srivastava |