Breast Cancer Diagnosis Using K-means ‎Methodology

Noor Kadhim Ayoob

doi:10.29196/jub.v26i1.348

Article Details

Breast Cancer Diagnosis Using K-means ‎Methodology

Authors:

Noor Kadhim Ayoob

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.26 Issue 1, pp.9-16

Document Type:

Article

Publication Date:

1/2018

Document Language:

English

Document ID (Org No.):

2001382350

pISSN:

2312-8135

DOI:

10.29196/jub.v26i1.348

Keywords:

classification‎

Abstract:

 After lung cancer, breast cancer is the second cause of death among women. Due to the seriousness of the disease, research has stepped up to help diagnose this disease by providing medical personnel with a classification based computer systems that determine whether the patient is infected. This research focuses on the use method (K-means) for the diagnosis of breast cancer based on a global database known as (WBCD) dedicated to this purpose. The proposed method has proved its effectiveness in classification and the accuracy of the system is equal to 96.4861%.

Article Details

Breast Cancer Diagnosis Using K-means ‎Methodology

Authors: Noor Kadhim Ayoob

Publisher: University of Babylon

Journal: JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.26 Issue 1, pp.9-16

Document Type: Article

Publication Date: 1/2018

Document Language: English

Document ID (Org No.): 2001382350

pISSN: 2312-8135

DOI: 10.29196/jub.v26i1.348

classification‎

Issues

Authors:

Noor Kadhim Ayoob

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.26 Issue 1, pp.9-16

Document Type:

Article

Publication Date:

1/2018

Document Language:

English

Document ID (Org No.):

2001382350

pISSN:

2312-8135

DOI:

10.29196/jub.v26i1.348