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: ExpressJS and Mongoose for building the API and managing server-side logic.
- Frontend: Kotlin with mobile-responsive and interactive user interface.
- AI/ML Model: TensorFlow for building the image classification model to detect skin diseases.
- Database: MongoDB for real-time database management and user data storage.
- 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
I was responsible for designing and implementing the backend API and managing cloud services.
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.