Organization repository: HealMe on GitHub
HealMe - Your Path to Faster, Smarter Wound Healing
Project Name
HealMe
Short Description
HealMe is a skin disease detection application that leverages AI to analyze images of skin conditions and provide users with accurate insights and recommendations for further medical consultation.
Purpose and Background
HealMe was created to help individuals identify and understand potential skin conditions through the power of AI. The app aims to provide users with an accessible, fast, and reliable tool to detect skin diseases at an early stage, promoting better healthcare outcomes by encouraging timely medical consultation.
Technologies Used
- Backend: Python with Flask for building the API and managing server-side logic.
- Frontend: React Native for a mobile-responsive and interactive user interface.
- AI/ML Model: TensorFlow for building the image classification model to detect skin diseases.
- Database: Firebase for real-time database management and user data storage.
- Authentication: Firebase Authentication for secure user login and profile management.
- Version Control: Git for managing code and collaboration.
Key Features
- Skin Condition Detection: Users can upload images of their skin and get insights on potential skin conditions using an AI-powered image classification model.
- Recommendations and Advice: Based on the analysis, the app provides recommendations for medical consultation or home care.
- User Profiles: Allows users to create accounts and keep track of their skin condition history.
- Real-time Results: Provides instant feedback and suggestions after analyzing skin images.
Challenges and Solutions
A significant challenge was developing an accurate AI model to correctly classify skin conditions from images. This was addressed by training the model with a large dataset of labeled skin disease images, ensuring better accuracy. Additionally, implementing real-time image processing for fast feedback was optimized to enhance the user experience.
Roles and Responsibilities
As the lead developer, I was responsible for designing and implementing the backend API, training the AI model, developing the mobile app, and integrating the entire system to deliver a seamless user experience.
Outcomes and Impact
The application has been successfully deployed and tested, providing users with a convenient method for detecting potential skin conditions. Early feedback from users has been positive, particularly regarding the ease of use and the value of early detection for skin health.
Future Development
Plans for future development include expanding the dataset to improve the accuracy of the AI model, adding a feature for tracking skin health over time, and integrating telemedicine functionalities to allow users to consult with doctors directly through the app.