# Modification of intensive care unit data using analytical hierarchy process and fuzzy C-means model

Rusiman, Mohd Saifullah and Adnan, Robiah and Nasibov, Efendi and Jacob, Kavikumar (2012) Modification of intensive care unit data using analytical hierarchy process and fuzzy C-means model. Journal of Mathematics and System Science, 1 (1). pp. 1-6. ISSN 21595291

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## Abstract

This paper proposes a proper methodology in data modification by using analytical hierarchy process (AHP) technique and fuzzy c-mean (FCM) model in the Intensive Care Unit (ICU). The continuous data were built from binary data using analytical hierarchy process (AHP), whereas the binary data were created from continuous data using fuzzy c-means (FCM) model. The models used in this research are fuzzy c-regression models (FCRM). A case study in scale of health at an intensive care unit (ICU) ward using the AHP, FCM model and FCRM models was carried out. There are six independent variables involved in this study. There are four cases considered as a result of using AHP technique and FCM model toward independent data. After comparing the four cases, it was found that case 4 appeared to be the best model, having the lowest mean square error (MSE). The original data have the MSE value of 97.33, while the data of case 4 have MSE by 83.48. This means that the AHP technique can lower the MSE, while the FCM model cannot lower the MSE value. In other words, it can be proved that the AHP technique can increase the accuracy of prediction in modeling scale of health which is associated with the mortality rate in the ICU.

Item Type: Article Analytical hierarchy process (AHP); fuzzy c-means (FCM) model; fuzzy c-regression models (FCRM); mean square error (MSE) Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics Faculty of Applied Science and Technology > Department of Mathematics and Statistic Mr. Mohammad Shaifulrip Ithnin 13 Aug 2018 03:37 13 Aug 2018 03:37 http://eprints.uthm.edu.my/id/eprint/9373 View Download Statistic