SCIN-Dermatology-Raw-Images

This dataset contains 6,517 patient-submitted photographs organized into 3,061 clinical cases of common skin diseases. The source images are curated from the public Google Skin Condition Image Network (SCIN) corpus, cleansed of quality and gradability conflicts, and paired with complete patient-reported demographics, clinical symptoms, and dermatologist gradings.

Dataset Structure

This repository follows the standard Hugging Face ImageFolder structure:

.
├── README.md
├── metadata.csv
└── images/
    ├── -3205742176803893704.png
    ├── -4762289084741430925.png
    └── ...

The metadata.csv matches the image filenames in images/ to the respective case-level metadata and diagnostic splits.

Metadata Schema

Column Name	Data Type	Description
file_name	string	Relative path to the image, e.g. images/-3205742176803893704.png
case_id	string	Unique patient case ID
image_id	string	Unique image ID
fitzpatrick_skin_type	string	Fitzpatrick skin type grading (FST1–FST6)
monk_skin_tone_us	float	Monk Skin Tone grading (US standard, scale 1–10)
monk_skin_tone_india	float	Monk Skin Tone grading (India standard, scale 1–10)
age_group	string	Patient age category
sex_at_birth	string	Patient sex
primary_diagnosis	string	Primary consensus dermatology diagnosis (e.g. Eczema, Psoriasis)
binary_label	int	Triage label (0 = non-infectious, 1 = infectious)
symptoms_itching	boolean	Presence of itching symptom
symptoms_pain	boolean	Presence of pain symptom
condition_duration	string	Duration of the condition
dataset_split	string	Stratified split assignment (train, val, test)

Quick Start (Python)

To load and stream the images and metadata directly using the Hugging Face datasets library:

from datasets import load_dataset

# Load the dataset (automatically casts the 'image' field to PIL images)
dataset = load_dataset("HawkFranklin-Research/SCIN-Dermatology-Raw-Images")

# Access the training split
train_data = dataset["train"]

# Get the first sample
sample = train_data[0]
print(sample["primary_diagnosis"])  # e.g., 'Eczema'
print(sample["fitzpatrick_skin_type"])  # e.g., 'FST4'
sample["image"].show()  # Opens the PIL image

Citation & License

This dataset is distributed under the MIT License. The underlying image data and medical attributes are derived from the Google SCIN repository. If you use this dataset in your research, please cite the primary SCIN work:

@article{Ward2024_SCIN_JAMANetworkOpen,
  author    = {Ward, Edwin and others},
  title     = {Skin Condition Image Network (SCIN): A diverse dataset of patient-submitted skin photographs},
  journal   = {JAMA Network Open},
  year      = {2024},
  volume    = {7},
  number    = {5},
  pages     = {e2410389}
}