https://github.com/syedarsalan798/covid-tracker-app
The COVID-19 Tracker is a web application built with Flask that allows doctors and patients to track and manage COVID-19 cases. It provides functionalities for doctors to generate and forward results, and for patients to view their reports.
https://github.com/syedarsalan798/covid-tracker-app
bootstrap5 covid19-tracker flask-application machine-learning python scikitlearn-machine-learning sqlite-database tensorflow
Last synced: 3 months ago
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The COVID-19 Tracker is a web application built with Flask that allows doctors and patients to track and manage COVID-19 cases. It provides functionalities for doctors to generate and forward results, and for patients to view their reports.
- Host: GitHub
- URL: https://github.com/syedarsalan798/covid-tracker-app
- Owner: SyedArsalan798
- License: mit
- Created: 2023-07-12T06:54:56.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-07-12T09:33:18.000Z (almost 3 years ago)
- Last Synced: 2025-05-22T10:56:37.510Z (about 1 year ago)
- Topics: bootstrap5, covid19-tracker, flask-application, machine-learning, python, scikitlearn-machine-learning, sqlite-database, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 2.75 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# covid-tracker-app
The COVID-19 Tracker is a web application built with Flask that allows doctors and patients to track and manage COVID-19 cases. It provides functionalities for doctors to generate and forward results, and for patients to view their reports.
You can find already Trained Model on Google drive: [CNN_Covid19_Xray_V1.h5](https://drive.google.com/file/d/1GIz1F3G4p2sxWYFR8TYqSTNpl25NnX6Y/view?usp=sharing)
# Features
- **Doctor Dashboard:** Doctors can view a list of X-ray images uploaded by patients, generate results based on a machine learning model, and forward the results to patients.
- **Patient Dashboard:** Patients can view their X-ray images and the corresponding results generated by doctors.
- **Predictive Model:** The app uses a machine learning model to predict whether an X-ray image indicates COVID-19 or is normal.
- **SQLite3 Database:** The app utilizes a SQLite3 database to store X-ray images, patient information, and generated results.
# Technologies Used
- Flask: A Python web framework used for building the application.
- SQLite3: A lightweight database management system used for data storage.
- Bootstrap: A front-end framework used for responsive and attractive UI.
- Machine Learning (ML): A trained ML model is used to predict COVID-19 cases based on X-ray images. You can find dataset [here](https://www.kaggle.com/datasets/tawsifurrahman/covid19-radiography-database).
# Installation and Setup
- Clone the repository: `git clone `
- Create a virtual environment: `python -m venv venv`
- Activate the virtual environment: `source venv/bin/activate` (for Linux/Mac) or `venv\Scripts\activate` (for Windows)
- Install the required dependencies: `pip install -r requirements.txt`
- Run the Flask application: `flask run`
# Usage
- Access the web application at [http://localhost:5000](http://localhost:5000) (or as per Flask's default configuration).
- Doctors can log in, view X-ray images, generate results, and forward them to patients.
- Patients can log in, view their X-ray images, and check the generated results.
# Contributing
Contributions are welcome! Please fork the repository and submit a pull request with your proposed changes.
# License
This project is licensed under the MIT License.