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MalamaAI – Skin Disease Detection

MalamaAI – Skin Disease Detection

MalamaAI is a machine learning-powered application designed to recognize a variety of skin diseases using state-of-the-art computer vision techniques. The name “Malama”, meaning “to care for” in Hawaiian, reflects the project’s goal — to extend the reach of early detection and care through accessible technology.

At the heart of MalamaAI is a custom AI pipeline that builds upon a fine-tuned version of DinoV2, a robust self-supervised vision transformer. To further enhance its diagnostic capabilities, we integrated the Llama 3.370b language model, enabling the system to generate human-readable, context-aware reports based on image analysis results.

Features:

  • Interactive Frontend: Built using Next.js for a responsive and smooth user experience.
  • Scalable Backend: Flask-powered API server that efficiently handles image uploads and model inference.
  • Enhanced Model Stack: Fine-tuned DinoV2 for image classification, combined with Llama 3.370b for natural language explanations and guidance.

MalamaAI aims to support users with accessible, AI-powered insights into their skin health. While not a substitute for medical professionals, the tool is a step toward democratizing health diagnostics using machine learning.

Technologies Used:

  • DinoV2 (fine-tuned)
  • Llama 3.370b
  • Next.js
  • Flask
  • RESTful API integration