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Male Hair Loss Dataset - 2 400+ images

Dataset comprises medical images of scalps from five angles, labeled with seven classifications based on the Norwood-Hamilton scale, aiding in diagnosing hair losses and scalp conditions. Utilizing deep learning techniques, machine learning algorithms can analyze hair density, follicles, and hair growth patterns to improve accurate diagnosis of alopecia areata and other hair disorders. β€” Get the data

Dataset characteristics:

Characteristic Data
Description Photos of people with varying degrees of hair loss for alopecia classification
Data types Image
Tasks Classification, Machine Learning
Number of images 2,400
Number of files in a set 5 images (full-face photo, view from the top, back of the head, left side, and right side)
Total number of people 480
Labeling Metadata (gender, age, ethnicity)
Age Min = 18, max = 80, mean = 45

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Dataset structure

  • 1 β€” images of first person
  • 2 β€” images of second person
  • 3 β€” images of third person
  • annotation.json β€”file contains metadata and labels for all individuals in the dataset.

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