🧠 Multiple Disease Prediction

Multiple Disease Prediction is a machine learning-powered web application that allows users to predict the likelihood of multiple diseases— Diabetes and Heart Disease based on inputted clinical data. The models are trained using standard datasets and the app is deployed using Streamlit for an interactive user experience.

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🚀 Features

• Disease Prediction: Predicts the likelihood of

  • 🩸 Diabetes
  • ❤️ Heart Disease

• Streamlit Interface: Simple, interactive UI for inputting parameters and viewing results.

• Google Colab Training: ML models trained in Colab and exported as .sav files.

• Preprocessing with Scaler: Ensures consistent input handling using a saved scaler.pkl.

• Modular Structure: Clean folder layout for models, notebooks, and app logic.

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🧰 Getting Started

To get the Multiple Disease Prediction app running locally, follow the instructions below to set up the application on your local machine.

✅ Prerequisites

Ensure you have the following installed:

• Python 3.8+
• pip (Python package manager)
• Git (optional, for cloning)

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1. Clone the Repository

git clone https://github.com/tanmay-srivastav4/multiple-disease-prediction.git
cd multiple-disease-prediction

2. Create Virtual Environment (Optional)

For Windows

python -m venv venv
venv\Scripts\activate

For Mac/Linux

python3 -m venv venv
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Run the Application

streamlit run app.py

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🧰 Technologies Used

1. Frontend: Streamlit
2. Backend: Python
3. ML Libraries: scikit-learn, pandas, numpy
4. Model Training: Google Colab
5. Model Serialization: joblib (.sav format)