Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/23259
Title: | A Breast Disease Pre-Diagnosis Using Rule-based Classification |
Authors: | Suriana Ismail Roslan Ismail Tengku Elisa Najiha Tengku Sifizul |
Keywords: | Brease disease Rule-Based Artificial Intelligence |
Issue Date: | 4-Dec-2019 |
Abstract: | The Manual detection of breast disease cannot detect occurrences of potential high risk problem for a patient at the early stage. Since it is a commonly found disease among women, it is critical to overcome the problem as fast as possible. In this paper the design of the proposed Rule Based System will be presented and the symptoms of the breast cancer disease and possible ways to prevent it will be outlined. The proposed Rule Based System was produced to help people to Prevent and early detection breast cancer, because it is known that this disease does not have medication or cure yet. Android and web application are the two platform used in the designing of the proposed ruled based system. The application to breast cancer pre-diagnosis utilizes the features of each highly potential symptoms, obtained from patient perceived condition, to discriminate benign from malignant breast lumps. This allows an accurate pre-diagnosis without the urgency need for a surgical biopsy. |
URI: | http://ir.unikl.edu.my/jspui/handle/123456789/23259 |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
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Suriana Ismail Breast Disease.pdf | 169.77 kB | Adobe PDF | View/Open Request a copy |
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