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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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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