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

B. Oh; Y. S. Chu; S. Lee; S. G. Lee; K. Y. Chung; M. R. Roh; K. D. Seo; S. Yang

doi:10.1117/12.2648034

14 March 2023 Deep learning algorithms for predicting basement membrane involvement of acral lentiginous melanomas

B. Oh, Y. S. Chu, S. Lee, S. G. Lee, K. Y. Chung, M. R. Roh, K. D. Seo, S. Yang

Proceedings Volume 12352, Photonics in Dermatology and Plastic Surgery 2023; 123520D (2023) https://doi.org/10.1117/12.2648034
Event: SPIE BiOS, 2023, San Francisco, California, United States

Conference Poster

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.

Citation Download Citation

B. Oh, Y. S. Chu, S. Lee, S. G. Lee, K. Y. Chung, M. R. Roh, K. D. Seo, and S. Yang "Deep learning algorithms for predicting basement membrane involvement of acral lentiginous melanomas", Proc. SPIE 12352, Photonics in Dermatology and Plastic Surgery 2023, 123520D (14 March 2023); https://doi.org/10.1117/12.2648034

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