Hospitalization patient forecasting based on multi-task deep learning - Zhou, Min; Huang, Xiaoxiao; Liu, Haipeng; Zheng, Dingchang (Zielona Góra: Uniwersytet Zielonogórski)
Forecasting the number of hospitalization patients is important for hospital management. The number of hospitalization patients depends on three types of patients, namely, admission patients, discharged patients, and inpatients. However, previous works focused on one type of patients rather than the three types of patients together. In this paper, we propose a multi-task forecasting model to forecast the three types of patients simultaneously.
Keywords: hospitalization patients; forecasting; neutral networks; multitask learning