Aided diagnosis methods of breast cancer based on machine learning

被引：2
|
作者：
Zhao, Yue [1 ]
Wang, Nian [1 ]
Cui, Xiaoyu [1 ]
机构：
[1] Northeastern Univ, Sino Dutch Biomed & Informat Engn Sch, Shenyang, Liaoning, Peoples R China
来源：
2ND ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2017) | 2017年 / 887卷
基金：
中国国家自然科学基金;
关键词：
SYSTEM; RULES;
D O I：
10.1088/1742-6596/887/1/012072
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the field of medicine, quickly and accurately determining whether the patient is malignant or benign is the key to treatment. In this paper, K-Nearest Neighbor, Linear Discriminant Analysis, Logistic Regression were applied to predict the classification of thyroid, Her-2, PR, ER, Ki67, metastasis and lymph nodes in breast cancer, in order to recognize the benign and malignant breast tumors and achieve the purpose of aided diagnosis of breast cancer. The results showed that the highest classification accuracy of LDA was 88.56%, while the classification effect of KNN and Logistic Regression were better than that of LDA, the best accuracy reached 96.30%.
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页数：6
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