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Prediction of Breast Cancer Risk Level with Risk Factors in Perspective to Bangladeshi Women using Data Mining
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 82 - Number 4 |
| Year of Publication: 2013 |
| Authors: Kawsar Ahmed, Md. Ahsan Habib, Tasnuba Jesmin, Md. Zamilur Rahman, Md. Badrul Alam Miah |
10.5120/14107-2147
|
Kawsar Ahmed, Md. Ahsan Habib, Tasnuba Jesmin, Md. Zamilur Rahman, Md. Badrul Alam Miah . Prediction of Breast Cancer Risk Level with Risk Factors in Perspective to Bangladeshi Women using Data Mining. International Journal of Computer Applications. 82, 4 ( November 2013), 36-41. DOI=10.5120/14107-2147
Abstract
The upgraded and modern medical technologies are the most challenging task to detect cancer and provide accurate treatment. In Bangladesh about two million women are affected by 2nd most occurring deathful breast cancer due to them and their family member's unconsciousness and poverty. It requires about $400-500 for proper diagnosis and treatment. Most of the Bangladeshi women are uneducated and feel shy with society or husband to go doctor for checking breast cancer. So it also will be a good achievement of this work to find breast cancer with more efficiency. Breast cancer depends on some risk factors that may help to detect breast cancer using multi-layered approach. In this work, at first it is collected 100 peoples' information which consist of both cancer and non-cancer information having missing or duplicate information. So pre-processing and K-means clustering methods are performed to separate relevant and non-relevant data to Breast Cancer. Then risk factors are ranked using WEKA tools and are assigned a score according to rank. Finally, it is implemented an application software using Lotus Notes to predict Breast Cancer risk level which is easier, effective, efficient, secured, cheap and time saving with some suggestions. This technique will contribute equal opportunity to the underdeveloped and developing countries to detect, diagnosis, and treatment of breast cancer.
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