Organized and cleaned metadata for skin lesions from the ISIC 2019 challenge. The data is intended for binary and multi-class classification tasks. The original source is the International Skin Imaging Collaboration archive.
Use Cases
- Train binary classifiers for benign vs. malignant lesions based on organized metadata.
- Develop multi-class disease classification models for various skin conditions.
- Benchmark model performance on a standardized, cleaned version of the ISIC 2019 dataset.
Strengths
- Data is described as organized and cleaned, suggesting preprocessing for usability.
- Derived from the ISIC archive, a known source for dermatological imaging research.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Last update date is unknown; freshness unverified.
Provenance
- Source
- International Skin Imaging Collaboration (ISIC) archive.
- Collection Method
- Metadata from the ISIC 2019 challenge, organized and cleaned.