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Deep learning algorithms for predicting basement membrane involvement of acral lentiginous melanomas

Authors
 B. Oh  ;  Y. S. Chu  ;  S. Lee  ;  S. G. Lee  ;  K. Y. Chung  ;  M. R. Roh  ;  K. D. Seo  ;  S. Yang 
Citation
 Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol.12352 : 123520D, 2023-03 
Journal Title
Progress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN
 1605-7422 
Issue Date
2023-03
Abstract
In Asians, melanoma appears as pigmented lesions on the hands and feet, and is often diagnosed as acral malignant melanoma (ALM) in the late stage with a very poor prognosis. Among diverse clinical characteristics of melanoma, the presence of basement membrane involvement is one of the most important prognostic factors. However, there have been few studies reporting artificial intelligence for prediction of basement membrane involvement in ALMs beyond its diagnosis. Therefore, in this study, we present a deep learning model that predicts the basement membrane involvement of ALMs from dermoscopy images. © 2023 SPIE.
Full Text
https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12352/2648034/Deep-learning-algorithms-for-predicting-basement-membrane-involvement-of-acral/10.1117/12.2648034.short
DOI
10.1117/12.2648034
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Dermatology (피부과학교실) > 1. Journal Papers
Yonsei Authors
Oh, Byung Ho(오병호) ORCID logo https://orcid.org/0000-0001-9575-5665
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/195408
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