Performance of a Machine Learning Algorithm on Lesions with a High Preoperative Suspicion of Invasive Melanoma
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Abstract
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MJS Publishing, Medical Journals Sweden AB
Reference17 articles.
1. Polesie S, Gillstedt M, Kittler H, Rinner C, Tschandl P, Paoli J. Assessment of melanoma thickness based on dermoscopy images: an open, web-based, international, diagnostic study. J Eur Acad Dermatol Venereol 2022; 36: 2002-2007.
2. https://doi.org/10.1111/jdv.18436
3. Polesie S, Jergeus E, Gillstedt M, Ceder H, Dahlen Gyllencreutz J, Fougelberg J, et al. Can dermoscopy be used to predict if a melanoma is in situ or invasive? Dermatol Pract Concept 2021; 11: e2021079.
4. https://doi.org/10.5826/dpc.1103a79
5. Polesie S, Sundback L, Gillstedt M, Ceder H, Dahlen Gyllencreutz J, Fougelberg J, et al. Interobserver agreement on dermoscopic features and their associations with in situ and invasive cutaneous melanomas. Acta Derm Venereol 2021; 101: adv00570.
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