1k citations · 1.3k across the 4 of their papers we have counts for
5 papers
A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein +21
Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient. Though artificial intelligence classification algo…
BCN20000: Dermoscopic Lesions in the Wild
Marc Combalia, Noel C. F. Codella, Veronica Rotemberg +8
This article summarizes the BCN20000 dataset, composed of 19424 dermoscopic images of skin lesions captured from 2010 to 2016 in the facilities of the Hospital Clínic in Barcelona.…
Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)
Noel Codella, Veronica Rotemberg, Philipp Tschandl +9
This work summarizes the results of the largest skin image analysis challenge in the world, hosted by the International Skin Imaging Collaboration (ISIC), a global partnership that…
Collaborative Human-AI (CHAI): Evidence-Based Interpretable Melanoma Classification in Dermoscopic Images
Noel C. F. Codella, Chung-Ching Lin, Allan Halpern +3
Automated dermoscopic image analysis has witnessed rapid growth in diagnostic performance. Yet adoption faces resistance, in part, because no evidence is provided to support decisi…
Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)
Noel C. F. Codella, David Gutman, M. Emre Celebi +8
This article describes the design, implementation, and results of the latest installment of the dermoscopic image analysis benchmark challenge. The goal is to support research and…