Multiple Regression And Multi-Server Queueing Approach to Public Health Care Systems
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Abstract
In this paper, we investigate the role of queueing models in evaluating and assessing the performance of health care systems. We propose multiple regression technique as machine learning for a multi-server queueing model to analyze the public health care system in order to build a mathematical relationship between predictor-variables and response variable. We apply the multiple regression analysis technique to predict the choice of patients regarding choosing public health care system on the basis of various predictor-variables represented as capacity of health care system, number of health experts, size of waiting line of patients, average cost of treatment etc.
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