Artificial Intelligence in Cutaneous Oncology

Skin cancer, previously known to be a common disease in Western countries, is becoming more common in Asian countries. Skin cancer differs from other carcinomas in that it is visible to our eyes. Although skin biopsy is essential for the diagnosis of skin cancer, decisions regarding whether or not t...

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Main Authors: Yu Seong Chu, Hong Gi An, Byung Ho Oh, Sejung Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Medicine
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fmed.2020.00318/full
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spelling doaj-faaddbec4b58481799620253f6f02b782020-11-25T03:44:31ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2020-07-01710.3389/fmed.2020.00318546145Artificial Intelligence in Cutaneous OncologyYu Seong Chu0Hong Gi An1Byung Ho Oh2Sejung Yang3Department of Biomedical Engineering, Yonsei University, Wonju, South KoreaDepartment of Biomedical Engineering, Yonsei University, Wonju, South KoreaDepartment of Dermatology and Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, South KoreaDepartment of Biomedical Engineering, Yonsei University, Wonju, South KoreaSkin cancer, previously known to be a common disease in Western countries, is becoming more common in Asian countries. Skin cancer differs from other carcinomas in that it is visible to our eyes. Although skin biopsy is essential for the diagnosis of skin cancer, decisions regarding whether or not to conduct a biopsy are made by an experienced dermatologist. From this perspective, it is easy to obtain and store photos using a smartphone, and artificial intelligence technologies developed to analyze these photos can represent a useful tool to complement the dermatologist's knowledge. In addition, the universal use of dermoscopy, which allows for non-invasive inspection of the upper dermal level of skin lesions with a usual 10-fold magnification, adds to the image storage and analysis techniques, foreshadowing breakthroughs in skin cancer diagnosis. Current problems include the inaccuracy of the available technology and resulting legal liabilities. This paper presents a comprehensive review of the clinical applications of artificial intelligence and a discussion on how it can be implemented in the field of cutaneous oncology.https://www.frontiersin.org/article/10.3389/fmed.2020.00318/fullartificial intellegencecutaneous oncologyskin cancermachine learningdeep learning
collection DOAJ
language English
format Article
sources DOAJ
author Yu Seong Chu
Hong Gi An
Byung Ho Oh
Sejung Yang
spellingShingle Yu Seong Chu
Hong Gi An
Byung Ho Oh
Sejung Yang
Artificial Intelligence in Cutaneous Oncology
Frontiers in Medicine
artificial intellegence
cutaneous oncology
skin cancer
machine learning
deep learning
author_facet Yu Seong Chu
Hong Gi An
Byung Ho Oh
Sejung Yang
author_sort Yu Seong Chu
title Artificial Intelligence in Cutaneous Oncology
title_short Artificial Intelligence in Cutaneous Oncology
title_full Artificial Intelligence in Cutaneous Oncology
title_fullStr Artificial Intelligence in Cutaneous Oncology
title_full_unstemmed Artificial Intelligence in Cutaneous Oncology
title_sort artificial intelligence in cutaneous oncology
publisher Frontiers Media S.A.
series Frontiers in Medicine
issn 2296-858X
publishDate 2020-07-01
description Skin cancer, previously known to be a common disease in Western countries, is becoming more common in Asian countries. Skin cancer differs from other carcinomas in that it is visible to our eyes. Although skin biopsy is essential for the diagnosis of skin cancer, decisions regarding whether or not to conduct a biopsy are made by an experienced dermatologist. From this perspective, it is easy to obtain and store photos using a smartphone, and artificial intelligence technologies developed to analyze these photos can represent a useful tool to complement the dermatologist's knowledge. In addition, the universal use of dermoscopy, which allows for non-invasive inspection of the upper dermal level of skin lesions with a usual 10-fold magnification, adds to the image storage and analysis techniques, foreshadowing breakthroughs in skin cancer diagnosis. Current problems include the inaccuracy of the available technology and resulting legal liabilities. This paper presents a comprehensive review of the clinical applications of artificial intelligence and a discussion on how it can be implemented in the field of cutaneous oncology.
topic artificial intellegence
cutaneous oncology
skin cancer
machine learning
deep learning
url https://www.frontiersin.org/article/10.3389/fmed.2020.00318/full
work_keys_str_mv AT yuseongchu artificialintelligenceincutaneousoncology
AT honggian artificialintelligenceincutaneousoncology
AT byunghooh artificialintelligenceincutaneousoncology
AT sejungyang artificialintelligenceincutaneousoncology
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