Published on in Vol 7, No 1 (2019): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10788, first published .
Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach

Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach

Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach

Rumeng Li   1 , MS ;   Baotian Hu   2 , PhD ;   Feifan Liu   3 , PhD ;   Weisong Liu   2 , PhD ;   Francesca Cunningham   4 , PharmD ;   David D McManus   3, 5 , MSc, MD ;   Hong Yu   1, 2, 3, 6 , PhD

1 College of Information and Computer Science, University of Massachusetts Amherst, Amherst, MA, United States

2 Department of Computer Science, University of Massachusetts Lowell, Lowell, MA, United States

3 Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States

4 Department of Veterans Affairs, Center for Medication Safety, Hines, IL, United States

5 Cardiology Division, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States

6 Center for Healthcare Organization and Implementation Research, Bedford Veterans Affairs Medical Center, Bedford, MA, United States

Corresponding Author:

  • Hong Yu, PhD
  • Department of Computer Science
  • University of Massachusetts Lowell
  • 1 University Avenue
  • Lowell, MA, 01854
  • United States
  • Phone: 1 9789343620
  • Fax: 1 9789343551
  • Email: hong_yu@uml.edu