Demand forecasting for platelet usage: From univariate time series to multivariable models

This study is the first to utilize different methods from statistical time series models to data-driven regression and machine learning techniques for platelet transfusion using clinical predictors and with different amounts of data. We find that the multivariable approaches have the highest accuracy in general, however, if sufficient data are available, a simpler time series approach appears to be sufficient. We also comment on the approach to choose predictors for the multivariable models.
Source: PLoS One - Category: Biomedical Science Authors: Source Type: research