Title : Prediction In-Hospital Cardiac Arrest within 8 hours using Vital signs
Published in : The 16th Asia Pacific International Conference
on Information Science and Technology (APIC-IST 2021)
Author : Minsu Chae, Sangwook Han, Hyo-Wook Gil, Jun Ma, Min Hong, HwaMin Lee
Corresponding author : HwaMin Lee
Location : Paradise Hotel Busan, Korea
The rapid response system in the hospital uses the early warning score (EWS) to predict in-hospital cardiac arrest. However, the traditional EWS has low precision and low recall. Since the precision is less than 4%, there has a problem with false alarms. We performed a retrospective cohort study in Soonchunhyang University Cheonan Hospital, which is a tertiary teaching hospital in the Republic of Korea. We performed by changing the data slice size to 8, 16, 24, 32, 40, 48, 56 hours. The deep learning model implemented in this paper has higher precision and recall than the traditional EWS.
This research was supported by Basic Science Research Program and the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (NRF-2021R1A2C1009290 & No. NRF-2019M3E5D1A02069073). This research was supported by X-mind Corps program of National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT (No. 2019H1D8A1105622)