Deep-learning model for screening sepsis using electrocardiography.

Joon-Myoung KwonYe Rang LeeMin-Seung JungYoon-Ji LeeYong-Yeon JoDa-Young KangSoo Youn LeeYong-Hyeon ChoJae-Hyun ShinJang-Hyeon BanKyung-Hee Kim

Published in: Scandinavian journal of trauma, resuscitation and emergency medicine (2021)

The DLM delivered reasonable performance for sepsis screening using 12-, 6-, and single-lead ECGs. The results suggest that sepsis can be screened using not only conventional ECG devices but also diverse life-type ECG machines employing the DLM, thereby preventing irreversible disease progression and mortality.

Keyphrases

septic shock
acute kidney injury
intensive care unit
deep learning
heart rate variability
heart rate
machine learning
risk factors
blood pressure
artificial intelligence
convolutional neural network