| --- |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| tags: |
| - medical |
| - dermatology |
| - education |
| - multimodal |
| pretty_name: ML Bootcamp — Skin Lesion Course Data |
| --- |
| |
| # ML Bootcamp — course data bundles |
|
|
| Teaching material for a three-week multimodal skin-lesion classification course |
| at Hongik University. Distributed as checksum-verified archives that the course |
| starter repository downloads and validates. |
|
|
| | Bundle | Contents | |
| | --- | --- | |
| | `standard.tar.gz` | training and development split — clinical images plus patient/lesion metadata, labeled | |
| | `public_leaderboard.tar.gz` | development leaderboard inputs — **unlabeled** | |
|
|
| Labels for the leaderboard set are not published; they stay with the course |
| staff, and submissions are scored offline. |
|
|
| ## Source and attribution |
|
|
| Derived from **PAD-UFES-20**, released under CC BY 4.0: |
|
|
| > Pacheco, A. G. C. et al. *PAD-UFES-20: A skin lesion dataset composed of |
| > patient data and clinical images collected from smartphones.* Data in Brief, |
| > 2020. |
|
|
| This derivative is likewise CC BY 4.0. Changes from the source: patient-disjoint |
| partitioning, removal of diagnosis-leaking fields, renaming of samples to course |
| identifiers, and a mapping of the six diagnostic classes to a binary |
| cancer / non-cancer target. |
|
|
| ## Intended use |
|
|
| Educational only. **Not a clinical diagnostic tool.** Models trained on this |
| data must not be used for medical decisions. |
|
|
