Abstract
Abstract: Accurately predicting the length of stay of patients in hospital can have positive impacts on both financial and psychological conditions of patients. This can also help hospital administrations to perform effective and correct allocation of critical resources to patients. This work presents an ensemble modeling technique that can be used for accurate determination of length of stay of patients based on several factors that are obtained from hospital records. The multi model nature of the architecture, and the heterogeneity associated with the production model provides a high performing system that can handle the complex hospital data. Experiments were performed on the standard MIMIC III data. Comparisons were performed with the existing state of the art models from literature. Comparisons indicate that the proposed HMME model demonstrations accuracy levels of 95%, indicating that the model can be effectively deployed in hospitals for decision making purposes. Keywords: Length of state prediction; ensemble modeling; multi model architecture; MIMIC III; correlation based analysis
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