Time series monitoring of patient condition using deep learning.

Abstract

In this study, we applied deep learning model based Neural-ODE and GRU to actual medical data and examined whether it is possible to monitor patient conditions by, comparing them with outcome and severity indices. In routine care, records of clinical procedures and laboratory values are events that occur sporadically in the time series direction, and not all the values of variables are acquired at each time point. Therefore, we utilized a deep learning model with a structure that can handle sporadic inputs. This made it possible to associate latent variables changing over time with indicators of the patient's condition.