Nail Disease Detection

The Nail Disease Detection Dataset is a meticulously curated collection of high-quality images designed to aid in the development of advanced machine learning models for nail disease diagnosis. This dataset includes diverse visual samples across various nail conditions, offering a valuable resource for medical research, education, and AI-driven healthcare solutions.

Key Features

• Categories Covered:
  The dataset includes subfolders for each specific nail condition, ensuring easy navigation and targeted analysis:

  • Acral Lentiginous Melanoma
  • Healthy Nail
  • Onychogryphosis
  • Blue Finger
  • Clubbing
  • Pitting

• File Format:

  • Images are provided in JPEG format, a widely supported and versatile file type suitable for machine learning workflows.

Applications

1. Medical Image Analysis:
   • Facilitate the creation of AI-powered diagnostic tools for the early detection of nail diseases.
2. Machine Learning Training:
   • Train and validate classification models for accurate identification of nail conditions.
3. Educational Use:
   • Enhance the learning experience for medical students and researchers by providing a visual reference for various nail diseases.