M. M. M. Al-Nozha, A. Moheeb, A. R. Mohammed, K. Z. Mohamed, N. B. Khan, Y. Y. Al-Mazrou, M. A. Al-Maatouq, K. Al-Marzouki, A. Al-Khadra, M. S. Nouh, S. S. Al-Harthi, M. S. Al-Shahid and A. Al-Mobeireek, “Hypertension in Saudi Arabia,” Saudi Medical Journal, Vol. 28, No. 1, 2007, pp. 77-84.

has been cited by the following article:

• TITLE: Predictive Analysis on Hypertension Treatment using Data Mining Approach in Saudi Arabia

  AUTHORS: Abdullah A. Aljumah, Mohammed Gulam Ahamad, Mohammad Khubeb Siddiqui

  KEYWORDS: Hypertension, Data Mining, Regression, Residual Plots, Prediction

  JOURNAL NAME: Intelligent Information Management, Vol.3 No.6, October 31, 2011

  ABSTRACT: In the present investigation, the data sets of (Non Communicable Diseases) NCD risk factors a standard report of Saudi Arabia 2005 in collaboration with World Health Organisation have been employed for regression analysis using data mining technique and that leads to the prediction of which treatment contributes more to improvement in hypertension. The Oracle Data Miner (ODM) tool has been used for the analysis of data. The data sets for different age groups in case of blood pressure treatment for hypertension for Male using different modes have been studied. The age group is in between of 15 years to 64 years. Data mining is an appropriate and sufficiently sensitive method to analyze outcomes of which mode of treatment is more effective to which age group. The Oracle data miner predicts the best mode of treatment for each group by which one can analyse the appropriate treatment. The predictions are also been compared with the help of residual plots. The residual graphs have been correlated with the predictions.