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

Applications of AI (233) Clinical Informatics (1241) mHealth for Health Administration (182) Decision Support for Health Professionals (1451) Intensive Care Unit (ICU) (150) Machine Learning (1934) Cost-Effectiveness and Economics (326)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71247, first published .
A Real-Time Signal-Based Wavelet Long Short-Term Memory Method for Length-of-Stay Prediction for the Intensive Care Unit: Development and Evaluation Study

A Real-Time Signal-Based Wavelet Long Short-Term Memory Method for Length-of-Stay Prediction for the Intensive Care Unit: Development and Evaluation Study

A Real-Time Signal-Based Wavelet Long Short-Term Memory Method for Length-of-Stay Prediction for the Intensive Care Unit: Development and Evaluation Study

Authors of this article:

Yiqun Jiang1 Author Orcid Image ;   Qing Li1 Author Orcid Image ;   Wenli Zhang2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Yiqun Jiang   1 , PhD ;   Qing Li   1 , PhD ;   Wenli Zhang   2 , PhD

1 Industrial and Manufacturing Systems Engineering, College of Engineering, Iowa State University, Ames, IA, United States

2 Department of Information Systems and Business Analytics, Debbie and Jerry Ivy College of Business, Iowa State University, Ames, IA, United States

Corresponding Author:

  • Wenli Zhang, PhD
  • Department of Information Systems and Business Analytics
  • Debbie and Jerry Ivy College of Business, Iowa State University
  • 3332 Gerdin Business Building, 2167 Union Drive
  • Ames, IA 50011
  • United States
  • Phone: 1 5152942469
  • Email: wlzhang@iastate.edu