A mobile application to assist users in identifying skin diseases using machine learning and cloud computing. Built as part of the Bangkit Academy program (Google, Tokopedia, Gojek, Traveloka).

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Table of Contents

• About the Project
• Learning Paths
  • Machine Learning
  • Cloud Computing
  • Mobile Development
• Features
• Usage

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About the Project

DermaOne utilizes machine learning for image-based skin disease detection and cloud services to enhance accessibility. It also provides educational resources about detected diseases and maintains a history of user predictions.

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Learning Paths

Machine Learning

• Dataset: 1,159 images, 8 skin disease classes (e.g., cellulitis, impetigo).
• Model: CNN with TensorFlow, utilizing normalization, augmentation, and Adam optimization.
• Results: Visualized metrics for accuracy and performance evaluation.

Cloud Computing

• Google Cloud Platform: Used for cost monitoring, authentication, and resource storage.
• Storage Buckets: For image uploads and prediction results.
• Cloud Run: Hosts APIs for disease prediction and news features.

Mobile Development

• Android Studio: Kotlin-based app with seamless integration of machine learning and cloud services.
• Features: Google Sign-In, image upload for disease prediction, health news, and prediction history.

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Features

1. Skin Disease Detection:
   • Upload images via camera or gallery.
   • Obtain predictions with confidence scores.
2. Health Information:
   • Fetch and display news articles via NewsAPI.
3. Prediction History:
   • Store and review past predictions.
4. Authentication:
   • Email/password and Google OAuth login options.
5. User-Friendly Navigation:
   • Dashboard, Information Health, History, and Profile sections.

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Usage

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Built with passion by the DermaOne team.