This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1112) Electronic Health Records (867) Cardiology (81) Myocardial Infarction (Heart Attack) (34) Methods and Instruments in Medical Informatics (65) Artificial Intelligence (912) Coronary Heart Disease (63) Data Science (162) Machine Learning (1189)

Published on in Vol 24, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37486, first published .
Improving the Performance of Outcome Prediction for Inpatients With Acute Myocardial Infarction Based on Embedding Representation Learned From Electronic Medical Records: Development and Validation Study

Improving the Performance of Outcome Prediction for Inpatients With Acute Myocardial Infarction Based on Embedding Representation Learned From Electronic Medical Records: Development and Validation Study

Improving the Performance of Outcome Prediction for Inpatients With Acute Myocardial Infarction Based on Embedding Representation Learned From Electronic Medical Records: Development and Validation Study

Authors of this article:

Yanqun Huang 1, 2 Author Orcid Image ;   Zhimin Zheng 1, 2 Author Orcid Image ;   Moxuan Ma 1, 2 Author Orcid Image ;   Xin Xin 1, 2 Author Orcid Image ;   Honglei Liu 1, 2 Author Orcid Image ;   Xiaolu Fei 3 Author Orcid Image ;   Lan Wei 3 Author Orcid Image ;   Hui Chen 1, 2 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Huang Y, Wang M, Zheng Z, Ma M, Fei X, Wei L, Chen H. Representation of time-varying and time-invariant EMR data and its application in modeling outcome prediction for heart failure patients. Journal of Biomedical Informatics 2023;143:104427 View