Application Of Data Mining: Diabetes Health Care In Young And Old Patients
| المصدر: | مجلة جامعة الملك سعود - علوم الحاسب والمعلومات |
|---|---|
| الناشر: | جامعة الملك سعود |
| المؤلف الرئيسي: | Aljumah, Abdullah A. (Author) |
| مؤلفين آخرين: | Ahamad, Mohammed Gulam (Co-Author) , Siddiqui, Mohammad Khubeb (Co-Author) |
| المجلد/العدد: | مج25, ع2 |
| محكمة: | نعم |
| الدولة: |
السعودية |
| التاريخ الميلادي: |
2013
|
| الصفحات: | 127 - 136 |
| DOI: |
10.33948/0584-025-002-002 |
| ISSN: |
1319-1578 |
| رقم MD: | 972903 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | science |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Data Mining | Oracle Data Mining Tool | Prediction | Regression | Support Vector Machine | Diabetes Treatment
|
| رابط المحتوى: |
| المستخلص: |
This research concentrates upon predictive analysis of diabetic treatment using a regression- based data mining technique. The Oracle Data Miner (ODM) was employed as a software mining tool for predicting modes of treating diabetes. The support vector machine algorithm was used for experimental analysis. Datasets of Non Communicable Diseases (NCD) risk factors in Saudi Arabia were obtained from the World Health Organization (WHO) and used for analysis. The dataset was studied and analyzed to identify effectiveness of different treatment types for different age groups. The five age groups are consolidated into two age groups, denoted as p (y) and p(o) for the young and old age groups, respectively. Preferential orders of treatment were investigated. We conclude that drug treatment for patients in the young age group can be delayed to avoid side effects. In contrast, patients in the old age group should be prescribed drug treatment immediately, along with other treatments, because there are no other alternatives available. |
|---|---|
| ISSN: |
1319-1578 |
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