Application of multi-classification method of skin cancer based on dermoscopic image
Authors: 
Qian Chen, Min Li, Cheng Chen, Chen Chen, Xiaoyi LvAuthors Info & Claims
Qian Chen, Min Li, Cheng Chen, Chen Chen, Xiaoyi LvAuthors Info & ClaimsPages 438 - 442
Abstract
As a kind of cancer with high incidence, skin cancer seriously threatens people's life and health. Early detection, early diagnosis, and early treatment are one of the effective ways to increase the survival rate of patients with skin diseases. Therefore, this paper used the ResNet50 model as a feature extractor based on deep learning, and combined machine learning algorithms to explore the heterogeneity among multi-type of skin cancer, and tried to construct the best performance computer-aided diagnosis model. The research first used preprocessing techniques such as hair noise removal and data enhancement, and then achieved a classification accuracy of 90.497% on the public data set of ISIC2019. The proposed model effectively relieves the huge work pressure of dermatologists, and provides a reference for the better use of dermoscopic images for intelligent diagnosis and classification of skin cancer.
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- Application of multi-classification method of skin cancer based on dermoscopic image
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Published In
October 2021
593 pages
ISBN:9781450395588
DOI:10.1145/3500931
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Published: 22 December 2021
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ISAIMS 2021
ISAIMS 2021: 2nd International Symposium on Artificial Intelligence for Medicine Sciences
October 29 - 31, 2021
Beijing, China
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Overall Acceptance Rate 53 of 112 submissions, 47%
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