Early Detection of Superficial Basal-Cell Carcinoma Skin Cancer with Extraction Method ABCD Feature Based on Android
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Abstract
Basal Cell Carcinoma (KSB) is a deadly skin cancer that has become one of the most common diseases. This disease generally occurs in areas of the skin that are often exposed to sunlight such as the face and neck. Basal cell carcinoma usually appears after more than 40 years of age, although it can also be found in children and adolescents rarely. If not treated immediately, basal cell carcinoma will spread locally, resulting in substantial tissue damage which causes impaired function. So we need the right steps in handling it. The purpose of designing this application is to detect basal cell carcinoma skin cancer on an Android-based device. In Paper, the authors discusses ways to overcome this problem by using the ABCD Feature extraction and K-Nearest Neighbor (KNN) as a classification. This application has a user friendly application display because it was developed using a platform that can be used by all circles of science, so users do not need a qualified IT skills. The results of this study are beneficial to the community, which can be used by the community and can find out whether or not KSB is detected or not. From the results of tests that have been done, the results of feature extraction accuracy get an accuracy of 91,6%.
Publication details
- DOI
- 10.1109/icamimia47173.2019.9223382
- OpenAlex
- W3093782509
- Document type
- conference-paper
- Language
- EN
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