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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

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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 .

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# 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.