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An open source project dedicated towards providing high quality diagnosis for people unable to do so with a medical professional πŸ“Έ This app seamlessly blends React Native for the frontend with Python for the backend/AI model.

License: Apache License 2.0

JavaScript 22.53% Jupyter Notebook 48.21% Python 27.35% Dockerfile 1.92%

melanoma-detector's Introduction

Melanoma Detector πŸ“ΈπŸ’»

Project Overview

This is an open-source project dedicated to helping people living in regions with a lack of dermatologists! πŸš€ We've developed a Skin Cancer Detection App using React Native for the front end and TensorFlow, NumPy, and Python for the back end. The app empowers users to check if a naevus (mole) is benign or malignant.

Features

  • πŸ“· Camera Integration: Capture photos directly from your phone's camera.
  • πŸ”„ Real-time Detection: Instantly send the photo to the TensorFlow model for analysis.
  • πŸ€– Machine Learning Magic: Utilizing TensorFlow, NumPy, and Python to distinguish between benign and malignant moles.

How It Works

  1. πŸ“± User Permission: The app prompts the user for camera permissions.
  2. πŸ“Έ Capture Photo: Users can take photos of the naevus they want to analyze.
  3. πŸš€ Model Processing: The app sends the photo to the TensorFlow model for analysis.
  4. 🩺 Diagnosis Result: The model processes the image and provides feedback on whether the naevus is benign or malignant.

Technologies Used

  • βš›οΈ React Native: For the frontend development.
  • 🧠 TensorFlow: Powering the machine learning model.
  • 🐍 Python: Backend development and model training.
  • πŸ“Š NumPy: Handling numerical operations efficiently.
  • πŸ“· Expo: Leveraging the React Native's cross-platform capability

Training Data

  • πŸ“Š Kaggle Dataset: The model has been trained on a curated dataset from Kaggle, ensuring robust and accurate predictions.

Future Enhancements

  • 🌐 Web Deployment: I am considering deploying the app on the web for broader accessibility.
  • 🌈 Improved UX/UI: I plan to enhance the user interface with nativewind.

Acknowledgments

A big shoutout to the open-source community and the incredible tools and libraries that made this project possible. Special thanks to my team members for contributing so much to this project! πŸŽ‰

Also a big thank you to the authors of the

Melanoma and Nevus Skin Lesion Classification Using Handcraft and Deep Learning Feature Fusion via Mutual Information Measures

research paper for sharing their CAD system

Happy Coding! πŸš€πŸ‘©β€πŸ’»πŸ‘¨β€πŸ’»

Requirements

  • Android or iOS device with a camera
  • Internet connection for TensorFlow.js model updates (if applicable)

Installation

  1. Clone the repository:

    git clone https://github.com/VukIG/Melanoma-Detector.git
  2. Install dependencies:

    cd Melanoma-Detector
    npm install
  3. Run the app and Scan the QR code with the Expo app from Play Store :

    npx expo start --tunnel
  4. Run the app on your emulator ( Optional if you don't want to use the expo app ):

    Press w for web, a for android emulator ( Requires the AndroidSDK setup ) or i for ios emulator ( requires xcode )    

How to Contribute

Feel free to fork the repository and contribute to the development. Your suggestions and enhancements are more than welcome! πŸ™Œ

We welcome contributions! If you have suggestions, found a bug, or want to improve the app, please open an issue or submit a pull request.

License

This project is licensed under the Apache 2.0.

Detailed explanation

The detailed explanation on how this app should work is in Serbian and can be accessed through this url: https://docs.google.com/document/d/1NwlALtB-bNRuoXDWS3nWsnSi3bMCoCZO5Nre84uz1rA/edit?usp=sharing

melanoma-detector's People

Contributors

vukig avatar ttesseractt avatar riiich avatar omeeden avatar adrose108 avatar chriss0309 avatar amassablemovie4 avatar jbalcom44 avatar

Stargazers

Barrios7 avatar Riza avatar  avatar James Murdza avatar mohamed ben chikha avatar  avatar  avatar Shariq Malik avatar Akshitha Nagaraj avatar  avatar

Watchers

 avatar

melanoma-detector's Issues

Scroll feature on App

After booting up the expo app, there is an issue with the swipe feature going through the pages when swiping from right to left. Fix feature so swiping on both sides (right to left) and (left to right) work smoothly.

Error within the Checkbox component

Could you decide whether to replace the BouncyCheckbox library with a new one? The issue is with the styling of the component. When the user clicks on the gender checkbox the text gets crossed over and the color of the bubble filling is wrong. You should import colors and use colors.primarycolor . Make sure the check box can only check off one of the boxes

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