The self-organizing maps of Kohonen in the medical classification

被引：0

作者：

Zribi, Manel ^{[1
]}

Boujelbene, Younes ^{[1
]}

Abdelkafi, Ines ^{[2
]}

Feki, Rochdi ^{[2
]}

机构：

[1] Sfax Univ, Fac Econ & Management, URECA, Sfax, Tunisia

[2] Sfax Univ, URED, Sfax, Tunisia

来源：

2012 6TH INTERNATIONAL CONFERENCE ON SCIENCES OF ELECTRONICS, TECHNOLOGIES OF INFORMATION AND TELECOMMUNICATIONS (SETIT) | 2012年

关键词：

Classification; breast cancer; Kohonen self-organizing maps;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In Tunisia, breast cancer is the most common cancer among women; it presents the leading cause of female mortality in the age group 35 to 55 years. This paper uses a neural approach based on Kohonen self-organizing maps to perform a classification of tumors (benign and malignant) using a sample of Tunisian women. Empirical results demonstrate the relevance of the approach and show that neural networks are an important decision support technique for detecting the presence of cancerous tissue in the breast and the classification of tumors.

引用

页码：852 / 856

页数：5

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