This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. The stochastic and the artificial neural network techniques are commonly used in hydrology. However, in this study a novel technique for forecasting rainfall was established. Results from this study have proven that the theory of biological immune systems could be technically applied to time series data. Biological immune systems are nonlinear and chaotic in nature similar to the daily rainfall data. This study discovered that the proposed CSA was able to predict the daily rainfall data with an accuracy of 90% during the model training stage. In the testing stage, the results showed that an accuracy between the actual and the generated data was within the range of 75 to 92%. Thus, the CSA approach shows a new method in rainfall data prediction.
Hypertension represents a major burden in Asia, with a high prevalence rate but poor level of awareness and control reported in many countries in the region. Home blood pressure monitoring has been validated as an accurate and reliable measure of blood pressure that can help guide hypertension treatment as well as identify masked and white-coat hypertension. Despite its benefits, there has been limited research into home blood pressure monitoring in Asia. The authors reviewed the current evidence on home blood pressure monitoring in Asia, including but not limited to published literature, data presented at congresses, and national hypertension management guidelines to determine the current utilization of home blood pressure monitoring in clinical practice in the region. Public policies to enable greater access to home blood pressure monitoring and its use in clinical care would add considerably to improving hypertension outcomes in Asia.
BACKGROUND: Accurate measurement of renal function is important: however, radiolabelled gold standard measurement of GFR is highly expensive and can only be used on a very limited scale. We aim to compare the performance of Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equations in the multi-ethnic population attending University Malaya Medical Centre (UMMC).
METHODS: This is a cross-sectional study recruiting patients, who attend UMMC Nephrology clinics on voluntary basis. 51-Chromium EDTA (51Cr-EDTA) plasma level was used to measure the reference GFR. The serum creatinine was determined by IDMS reference modified Jaffe kinetic assay (CrJaffe). The predictive capabilities of MDRD and CKD-EPI based equations were calculated. Data was analysed using SPSS version 20 and correlation, bias, precision and accuracy were determined.
RESULTS: A total of 113 subjects with mean age of 58.12 ± 14.76 years and BMI of 25.99 ± 4.29 kg/m2 were recruited. The mean reference GFR was 66.98 ± 40.65 ml/min/1.73m2, while the estimated GFR based on MDRD and CKD-EPI formula were 62.17 ± 40.40, and 60.44 ± 34.59, respectively. Both MDRD and CKD-EPI were well-correlated with reference GFR (0.806 and 0.867 respectively) and statistically significant with p