REDESIGNING POST-OPERATIVE PROCESSES USING DATA MINING CLASSIFICATION TECHNIQUES

Data mining classification models are developed and investigated in this paper. These adopted to develop redesign several business processes based on post-operative data. Post-operative data were collected used via the Waikato Environment for Knowledge Analysis (WEKA), investigate factors influencing patients’ admission after surgery compare DM models. The results reveal that each implemented technique entails different attributes affecting post-surgery status. comparison suggests neural networks outperform other techniques. Further, optimal number of beds required accommodate patients is investigated. simulation was conducted using queuing theory software compute expected achieve zero waiting time. indicate queue length 1, which means one bed will be available due patient discharge.