A patient-centric dataset of images and metadata for identifying melanomas using clinical context
| Autor: | Konstantinos Lioprys, Alexander J. Stratigos, Philipp Tschandl, Brigid Betz-Stablein, Emmanouil Chousakos, Shenara Musthaq, Liam J Caffery, Jochen Weber, Pascale Guitera, Marc Combalia, Nicholas Kurtansky, Jabpani Nanda, David A. Gutman, Ofer Reiter, Stephen W. Dusza, Kivanc Kose, Brian Helba, Steve G. Langer, George Shih, Veronica Rotemberg, Harald Kittler, Allan C. Halpern, Noel C. F. Codella, Josep Malvehy, H. Peter Soyer |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Data Descriptor medicine.medical_specialty Science Context (language use) Library and Information Sciences Controlled studies Education 030207 dermatology & venereal diseases 03 medical and health sciences 0302 clinical medicine False positive paradox Skin cancer Medicine In patient business.industry Melanoma Skin manifestations medicine.disease Computer Science Applications Metadata Statistical classification Patient centric 030220 oncology & carcinogenesis Radiology Statistics Probability and Uncertainty business Information Systems |
| Zdroj: | Scientific Data, Vol 8, Iss 1, Pp 1-8 (2021) Scientific Data |
| ISSN: | 2052-4463 |
| Popis: | 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. Measurement(s) melanoma • Skin Lesion Technology Type(s) Dermoscopy • digital curation Factor Type(s) approximate age • sex • anatomic site Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13070345 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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