Consumer-Facing Dermatology AI Benchmark Across Fitzpatrick Skin Tones
First archived reproducibility release supporting the manuscript Diagnostic Performance of Consumer-Facing Artificial Intelligence Applications for Skin Cancer Across Fitzpatrick Skin Tones . Included Definitive identifiers and analysis-ready data for the 231-image Fitzpatrick17k primary cohort Data for the 252-image DDI external cohort Per-image outputs from AI Skin Scanner, Model Dermatol, ChatGPT, and Claude Diagnostic and benign/malignant adjudication dictionaries Reproducible R analysis scripts, result tables, and publication figures R environment and package-version records The complete analysis was rerun successfully before this releas
Resource information
- Format
- zip
- Original repository
- 21754439
- DOI
- 10.5281/zenodo.21754439
- Credit basis
- Creators in Zenodo record metadata
- Access
- Open files available from the original Zenodo deposit
- Last checked
- Nov 5, 2026
- License
- mit-license
- Last record update
- Nov 5, 2026
About this resource
First archived reproducibility release supporting the manuscript Diagnostic Performance of Consumer-Facing Artificial Intelligence Applications for Skin Cancer Across Fitzpatrick Skin Tones . Included Definitive identifiers and analysis-ready data for the 231-image Fitzpatrick17k primary cohort Data for the 252-image DDI external cohort Per-image outputs from AI Skin Scanner, Model Dermatol, ChatGPT, and Claude Diagnostic and benign/malignant adjudication dictionaries Reproducible R analysis scripts, result tables, and publication figures R environment and package-version records The complete analysis was rerun successfully before this release. Source images are not redistributed and must be obtained from the original Fitzpatrick17k and DDI repositories under their respective terms. Reproduction Rscript analysis/00_validate_inputs.R Rscript analysis/run_all.R