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

Decision Support for Health Professionals (1127) Data Science (223) Electronic Health Records (961) Machine Learning (1370) Natural Language Processing (636) Diabetes-specific EHR Improvements (29)

Published on in Vol 7, No 4 (2019): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14340, first published .
Automatic Detection of Hypoglycemic Events From the Electronic Health Record Notes of Diabetes Patients: Empirical Study

Automatic Detection of Hypoglycemic Events From the Electronic Health Record Notes of Diabetes Patients: Empirical Study

Automatic Detection of Hypoglycemic Events From the Electronic Health Record Notes of Diabetes Patients: Empirical Study

Authors of this article:

Yonghao Jin1 Author Orcid Image ;   Fei Li1 Author Orcid Image ;   Varsha G Vimalananda2, 3 Author Orcid Image ;   Hong Yu1, 2, 4, 5 Author Orcid Image
Article Authors Cited by (12) Tweetations (3) Metrics

Yonghao Jin   1 , BSc ;   Fei Li   1 , PhD ;   Varsha G Vimalananda   2, 3 , MPH, MD ;   Hong Yu   1, 2, 4, 5 , PhD

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

2 Center for Healthcare Organization and Implementation Research, Bedford, MA, United States

3 Section of Endocrinology, Diabetes and Metabolism, School of Medicine, Boston University, Boston, MA, United States

4 Department of Medicine, University of Massachusetts Medical School, Worcester, MA, United States

5 Department of Computer Science, University of Massachusetts Amherst, Amherst, MA, United States

Corresponding Author:

  • Hong Yu, PhD
  • Department of Computer Science
  • University of Massachusetts Lowell
  • 220 Pawtucket St
  • Lowell, MA, 01854
  • United States
  • Phone: 1 9789343620
  • Email: Hong_Yu@uml.edu