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

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
  2. Xie P, Wang H, Xiao J, Xu F, Liu J, Chen Z, Zhao W, Hou S, Wu D, Ma Y, Xiao J. Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study. Journal of Medical Internet Research 2024;26:e49848 View
  3. Huang Y, Chen S, Wang Y, Ou X, Yan H, Gan X, Wei Z. Comorbidity Patterns Analysis in Patients with Thyroid Disease Using Large-Scale Electronic Medical Records: Network-Based Study (Preprint). Interactive Journal of Medical Research 2023 View