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Disparities in dermatology AI performance on a diverse, curated clinical image set
An estimated 3 billion people lack access to dermatological care globally. Artificial intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However, most AI models have not been assessed on images of diverse skin tones or uncommon diseases. Thus, we created the Diverse De...
Autores principales: | Daneshjou, Roxana, Vodrahalli, Kailas, Novoa, Roberto A., Jenkins, Melissa, Liang, Weixin, Rotemberg, Veronica, Ko, Justin, Swetter, Susan M., Bailey, Elizabeth E., Gevaert, Olivier, Mukherjee, Pritam, Phung, Michelle, Yekrang, Kiana, Fong, Bradley, Sahasrabudhe, Rachna, Allerup, Johan A. C., Okata-Karigane, Utako, Zou, James, Chiou, Albert S. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9374341/ https://www.ncbi.nlm.nih.gov/pubmed/35960806 http://dx.doi.org/10.1126/sciadv.abq6147 |
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