An enhanced hybrid model for event prediction in healthcare time series

摘要

Nowadays, there is a large volume of time series data, which generates by different parts of the healthcare domain such as hospitals, medical organizations, and health centers. Time series event-based prediction (TsEP) has recently become an active research trend in the healthcare domain, which is widely served outcome of it by the healthcare decision-makers. Actually, a valid and reliable prediction can play an important and key role in the society for forewarning crisis and supporting health management. Hence, the main motivation of this paper is to offer an enhanced hybrid model to the TsEP in healthcare, which is named TsEP-TC. TsEP-TC contains three components (TC) that combines relevant concepts to weighting, fuzzy logic, and metaheuristics in the TsEP problem. Experimental results indicate that TsEP-TC can provide the superior performance in comparison to the previous prediction models in the healthcare and biomedical domains. Additionally, TsEP-TC model can be introduced as a useful way for handling the complex and uncertain behaviors of time series and fuzzy events predicting in healthcare.