Open AccessDevelopment and validation of a deep learning model to screen hypokalemia from electrocardiogram in emergency patients
Author(s) -
Chenxi Wang,
Yichu Zhang,
Qi-Lin Kong,
Zuxiang Wu,
Panpan Yang,
Cai-hua Zhu,
Shou-Lin Chen,
Tao Wu,
Qinghua Wu,
Qi Chen
Publication year - 2021
Publication title -
chinese medical journal/chinese medical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 63
eISSN - 2542-5641
pISSN - 0366-6999
DOI - 10.1097/cm9.0000000000001650
Subject(s) - hypokalemia , medicine , receiver operating characteristic , confidence interval , cardiology , emergency medicine , emergency department , psychiatry
A deep learning model (DLM) that enables non-invasive hypokalemia screening from an electrocardiogram (ECG) may improve the detection of this life-threatening condition. This study aimed to develop and evaluate the performance of a DLM for the detection of hypokalemia from the ECGs of emergency patients.