Disease Prediction from Symptoms

A robust system where users enter their symptoms, and the model predicts the possible disease. This project aims to assist in early disease detection and provide insights for medical consultation.

Features

• Symptom Input: Users can enter multiple symptoms they are experiencing.
• Disease Prediction: The model analyzes the symptoms and predicts the most likely disease.
• User-friendly Interface: Simple and intuitive interface for easy input and output visualization.

Installation

1. Clone the repository:

   git clone https://github.com/your-username/Disease-Prediction-from-Symptoms.git
   cd Disease-Prediction-from-Symptoms

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the application:

   streamlit run app.py

Usage

• Open the app in your browser.
• Enter the symptoms you are experiencing.
• View the predicted disease and possible next steps.

Architecture

1. Frontend: Built with Streamlit for an interactive user interface.
2. Backend: Utilizes a machine learning model trained on symptom and disease data to predict diseases.
3. Database: Stores symptom-disease mappings and user input data for analysis and improvement.

Screenshot

Contributing

We welcome contributions from the community. Please feel free to submit issues, feature requests, and pull requests.