Improving dataset transparency in dermatologic Artificial Intelligence using a dataset nutrition label.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 41193735.
- Also identified by DOI 10.1038/s41746-025-02125-9 and PMC identifier 12589650.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Biased and poorly documented dermatology datasets pose risks to the development of safe and generalizable artificial intelligence (AI) tools. We created a Dataset Nutrition Label (DNL) for multiple dermatology datasets to support transparent and responsible data use. The DNL offers a structured, digestible summary of key attributes, including metadata, limitations, and risks, enabling data users to better assess suitability and proactively address potential sources of bias in datasets.