In this paper we focus on prediction of health status of patients from the historical Electronic Health Records (EHR). We propose a multi-task framework that can monitor the multiple status of diagnoses. Patients’ historical records are fed into a Recurrent Neural Network (RNN) which memorizes all the past visit information, and then a task-specific layer is trained to predict multiple diagnoses. Experimental results show that prediction accuracy is reliable if compared to widely used approaches 1.
|Original language||English (US)|
|Journal||CEUR Workshop Proceedings|
|State||Published - Jan 1 2018|
|Event||26th Italian Symposium on Advanced Database Systems, SEBD 2018 - Castellaneta Marina (Taranto), Italy|
Duration: Jun 24 2018 → Jun 27 2018
All Science Journal Classification (ASJC) codes
- Computer Science(all)