Effective hypertensive treatment using data mining in Saudi Arabia

Abstract

In the present investigation, the data sets of NCD (Non Communicable Diseases) risk factors, a standard report of Saudi Arabia 2005, in collaboration with WHO (World Health Organisation) were employed. The Oracle Data Miner (ODM) tool was used for the analysis and prediction of data. The data sets for different age groups in case of blood pressure treatment for hypertension for male using different modes had been studied. The age group was in between of 15 and 64 years. Data mining had been an appropriate and sufficiently sensitive method to analyze the outcomes of which mode of treatment is more effective to which age group. The five age group of NCD data had been put into two age groups of young and old denoted as 'Y' and 'O' respectively. Data mining showed that all the five modes of treatments were effective for older people due to hypertension at older ages.

Level of awareness of Saudi medical students of the internet-based health-related information seeking and developing to support health services

“…E-health in Saudi Arabia is growing, as many organizational and individual initiatives have implemented e-health applications. Many studies are available in the literature about e-health in Saudi Arabia [ 10 – 34 ], however, data is limited to a few organizations and does not necessarily reflect the current and potential use of e-health for health care organizations in the country [ 35 ]. A descriptive analysis of the status of e-health in Saudi Arabia highlighted the national e-health initiatives such as the establishment of a new Master of Health Informatics degree program at King Saud bin-Abdulaziz University for Health Sciences (KSAU-HS) as an initiative to educate specialized professionals [ 11 ], with an e-health course to foster future professional development in this field in the country [ 15 ] and the role of the Saudi Association for Health Informatics (SAHI) in enhancing coordination among health information professionals [ 11 ].…”

Application of Receiver Operating Characteristics (ROC) on the Prediction of Obesity

“…In recent years, applications of data mining have been widely seen on the prediction of the best mode for the intervention of chronic diseases such as hypertension and diabetes. For this, the Oracle Data Miner (ODM) tool has been prominently used in order to explore the meaningful patterns for predicting the effective mode of intervention [18][19][20][21]. Few of the related works have been discussed here.…”

“…Different risk factors have been analyzed for hypertension interventions by Naïve Bayesian classifier and found quitting smoking is more effective [20]. A research was carried out to predict which type of treatment is more effective in hypertension using ODM and found that quitting smoking is an effective mode to prevent hypertension [21].…”

Principal Component Analysis Using For Estimating Hypertension

“…Diğer bir çalışmada, 15-64 yaş aralığındaki erkeklerin, belirlenen 5 tedavi çeşidinin hangi yaş aralığında daha etkin sonuç verdiğinin analizi için veri madenciliği algoritmaları kullanılmıştır (Almazyad, Ahamad, Siddiqui, & Almazyad, 2010).…”