https://github.com/tanvik-hub/multiple-disease-prediction-using-ml
This project is a Multiple Disease Prediction System that uses machine learning models to predict the likelihood of three diseases: Diabetes Heart Disease Parkinson's Disease The system is built using Support Vector Machines (SVM) and Logistic Regression models, providing an easy-to-use interface for users to input health parameters .
https://github.com/tanvik-hub/multiple-disease-prediction-using-ml
anaconda3 logistic-regression python spyder streamlit svm
Last synced: 6 months ago
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This project is a Multiple Disease Prediction System that uses machine learning models to predict the likelihood of three diseases: Diabetes Heart Disease Parkinson's Disease The system is built using Support Vector Machines (SVM) and Logistic Regression models, providing an easy-to-use interface for users to input health parameters .
- Host: GitHub
- URL: https://github.com/tanvik-hub/multiple-disease-prediction-using-ml
- Owner: Tanvik-hub
- Created: 2024-09-09T12:45:07.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-09T12:51:10.000Z (about 1 year ago)
- Last Synced: 2025-02-13T17:29:41.813Z (8 months ago)
- Topics: anaconda3, logistic-regression, python, spyder, streamlit, svm
- Language: Python
- Homepage:
- Size: 19.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Multiple Disease Prediction using ML
## Project Description
This project is a **Multiple Disease Prediction System** that uses machine learning models to predict the likelihood of three diseases:
- **Diabetes**
- **Heart Disease**
- **Parkinson's Disease**The system is built using **Support Vector Machines (SVM)** and **Logistic Regression** models, providing an easy-to-use interface for users to input health parameters and receive a prediction based on the trained models.
## Features
- **Diabetes Prediction**: Based on health metrics such as glucose levels, insulin levels, and BMI.
- **Heart Disease Prediction**: Based on attributes like age, cholesterol, and resting blood pressure.
- **Parkinson's Disease Prediction**: Based on vocal attributes like jitter, shimmer, and pitch.## Tech Stack
- **Frontend**: Built with **Streamlit** for an interactive web interface.
- **Backend**: Machine learning models developed using **scikit-learn**.
- **Models Used**:
- **SVM** for Diabetes and Heart Disease Prediction.
- **Logistic Regression** for Parkinson's Disease Prediction.