Hipertension Demand Forecasting Using Cross-Correlation and Lagged Multiple Linear Regression Models for Anticipating Health Resources Needs
Guillem Hernández Guillamet,
Beatriz López,
Oriol Estrada
et al.
Abstract:This article presents an algorithm that uses a combination of cross-correlation analysis and lagged multiple linear regression models to predict the time-series of future demand for clinical visits associated with a certain diagnosis, specifically hypertension, in the Catalan health-care system. The algorithm aims to provide a robust and explainable feature selection set of predictors. The study demonstrates that it is possible to predict demand associated with a diagnosis through the demand for previous clini… Show more
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