A patient-centric dataset of images and metadata for identifying melanomas using clinical context Journal Article


Authors: Rotemberg, V.; Kurtansky, N.; Betz-Stablein, B.; Caffery, L.; Chousakos, E.; Codella, N.; Combalia, M.; Dusza, S.; Guitera, P.; Gutman, D.; Halpern, A.; Helba, B.; Kittler, H.; Kose, K.; Langer, S.; Lioprys, K.; Malvehy, J.; Musthaq, S.; Nanda, J.; Reiter, O.; Shih, G.; Stratigos, A.; Tschandl, P.; Weber, J.; Soyer, H. P.
Article Title: A patient-centric dataset of images and metadata for identifying melanomas using clinical context
Abstract: Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient. Though artificial intelligence classification algorithms have achieved expert-level performance in controlled studies examining single images, in practice dermatologists base their judgment holistically from multiple lesions on the same patient. The 2020 SIIM-ISIC Melanoma Classification challenge dataset described herein was constructed to address this discrepancy between prior challenges and clinical practice, providing for each image in the dataset an identifier allowing lesions from the same patient to be mapped to one another. This patient-level contextual information is frequently used by clinicians to diagnose melanoma and is especially useful in ruling out false positives in patients with many atypical nevi. The dataset represents 2,056 patients (20.8% with at least one melanoma, 79.2% with zero melanomas) from three continents with an average of 16 lesions per patient, consisting of 33,126 dermoscopic images and 584 (1.8%) histopathologically confirmed melanomas compared with benign melanoma mimickers. © 2021, The Author(s).
Journal Title: Scientific Data
Volume: 8
ISSN: 2052-4463
Publisher: Nature Publishing Group  
Date Published: 2021-01-28
Start Page: 34
Language: English
DOI: 10.1038/s41597-021-00815-z
PUBMED: 33510154
PROVIDER: scopus
PMCID: PMC7843971
DOI/URL:
Notes: Data set -- Japbani Nanda's name is misspelled on the original publication -- Errata issued, see DOIs: 10.1038/s41597-021-00865-3 , 10.1038/s41597-021-00879-x -- Export Date: 1 March 2021 -- Source: Scopus
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  1. Allan C Halpern
    396 Halpern
  2. Stephen Dusza
    288 Dusza
  3. Kivanc Kose
    81 Kose
  4. Japbani Nanda
    14 Nanda
  5. Shenara Musthaq
    10 Musthaq
  6. Jochen Weber
    15 Weber