Diversity in Dermatology Datasets: What Next?

The document highlights the need for improved diversity in dermatology datasets, particularly concerning ethnic representation and skin tone categorization. Current systems, like the Fitzpatrick phototyping system, have limitations, especially for darker skin types. A literature review reveals a lack of full ethnic representation in cutaneous imaging datasets and discrepancies in disease labeling. The COVID-19 pandemic has underscored racial disparities, prompting evaluations of clinical skin categorization systems. The scarcity of images representing darker skin in medical resources poses challenges for clinician and AI training. To prevent bias and inequality, the development of standardized language and taxonomy for skin color and ethnic categorization is essential.