Breast Cancer Classification Using Deep Learning

被引：0

作者：

Jasmir ^{[1
]}

Nurmaini, Siti ^{[2
]}

Malik, Reza Firsandaya ^{[3
]}

Abidin, Dodo Zaenal ^{[1
]}

Zarkasi, Ahmad ^{[2
]}

Kunang, Yesi Novaria ^{[4
]}

Firdaus ^{[2
]}

机构：

[1] STIKOM Dinamika Bangsa, Comp Engn, Intelligent Syst Res Grp, Jambi, Indonesia

[2] Sriwijaya Univ, Intelligence Syst Res Grp, Fac Comp Sci, Palembang, Indonesia

[3] Sriwijaya Univ, Fac Comp Sci, Palembang, Indonesia

[4] Bina Darma Univ, Intelligent Syst Res Grp, Palembang, Indonesia

来源：

2018 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND COMPUTER SCIENCE (ICECOS) | 2018年

关键词：

breast cancer; deep learning; multilayer perceptron; classification;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Breast cancer has been identified as the most widespread cancer amongst women and also the major cause of female cancer death all over the world. In this paper, we build the classification model of a person who is exposed to breast cancer based on recurrences-event and no-recurrences event. This classification using datasets from the University of Medicine Center, Institute Of Oncology, Ljublijana, Yugoslavia of the 286 datasets consist 2 classes, 201 No-Recurrences Events classes, 85 Recurrences-events classes and 10 attributes including classes. The algorithm used for breast cancer classification is the Multilayer Perceptron algorithm with the accuracy level of 96.5% and high evaluation is 69.93% in 8-fold cross validation from 10-fold cross validation.

引用

页码：237 / 241

页数：5

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