An open API service indexing awesome lists of open source software.

https://github.com/machinelearningprodigy/covid-19-detection-system

It is a Flask-based web application that predicts the likelihood of COVID-19 infection based on user symptoms. The app utilizes a K-Nearest Neighbors (KNN) model trained on relevant medical features to assess COVID-19 risk.
https://github.com/machinelearningprodigy/covid-19-detection-system

algorithms feature-engineering flask machine-learning numpy pandas scikit-learn

Last synced: about 2 months ago
JSON representation

It is a Flask-based web application that predicts the likelihood of COVID-19 infection based on user symptoms. The app utilizes a K-Nearest Neighbors (KNN) model trained on relevant medical features to assess COVID-19 risk.

Awesome Lists containing this project

README

          

# 🦠 COVID-19 Prediction App

Welcome to the **COVID-19 Prediction App**, a Flask-based web application that predicts the likelihood of COVID-19 infection based on user symptoms. The app utilizes a **K-Nearest Neighbors (KNN)** model trained on relevant medical features to assess COVID-19 risk.

## 🚀 Features

- **User-Friendly Web Interface** – Enter symptoms easily through a form.
- **Machine Learning Model** – Uses a **KNN classifier** to predict COVID-19 risk.
- **Instant Predictions** – Receive real-time results upon submission.
- **Flask Backend** – Lightweight and efficient backend for processing user input.

## 📊 How It Works

1. Select **symptoms** from the interactive form (e.g., Fever, Cough, Breathing Problems).
2. Click the **"Predict"** button to check the likelihood of COVID-19 infection.
3. View results:
- 🟢 **Low Risk** (No COVID-19)
- 🔴 **High Risk** (Possible COVID-19)

## 🛠 Installation & Usage

To run this Flask app locally, follow these steps:

### 1️⃣ Clone the Repository

```bash
git clone https://github.com/machinelearningprodigy/covid-19-detection-system.git
cd covid-19-detection-system
```

### 2️⃣ Install Dependencies

Ensure you have Python installed, then run:

```bash
pip install -r requirements.txt
```

### 3️⃣ Run the Flask App

```bash
python app.py
```

The app will be available at `http://127.0.0.1:5000/`.

## 🏗 Technologies Used

- **Python 3.x**
- **Flask** (for the web framework)
- **Scikit-learn** (for KNN model)
- **NumPy & Pandas** (for data processing)
- **HTML/CSS** (for frontend templates)

## 📦 Requirements

Ensure you have the following dependencies installed:

```txt
Flask==2.2.2
numpy==1.23.3
pandas==1.5.0
scikit-learn==1.1.2
```

## 🎯 Future Enhancements

- ✅ Improve model accuracy with additional data.
- ✅ Enhance UI with **Bootstrap/TailwindCSS**.
- ✅ Deploy the app on **Heroku/Render** for public access.

## 🤝 Contributing

Want to improve this project? Fork the repo, make changes, and submit a pull request!

## 📜 License

This project is open-source and available under the **MIT License**.

---

📧 **Need help?** Feel free to reach out or raise an issue in the repository! 🚀