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

#xHealthInformatics (10) Secondary Use of Clinical Data for Research and Surveillance (318) Natural Language Processing (637) Clinical Information and Decision Making (1315) Electronic Health Records (961) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (143) Big Data (216) Clinical Informatics (904) Safety and Error Prevention in Health (186) #xMedicalEthics (1)

Published on in Vol 2, No 3 (2021): Jul-Sep

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/2021.01.05.21249239v1, first published .
Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method

Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method

Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method

Authors of this article:

Roselie A Bright1 Author Orcid Image ;   Summer K Rankin2 Author Orcid Image ;   Katherine Dowdy2 Author Orcid Image ;   Sergey V Blok2 Author Orcid Image ;   Susan J Bright3 Author Orcid Image ;   Lee Anne M Palmer3 Author Orcid Image
Article Authors Cited by (6) Tweetations (16) Metrics

Roselie A Bright   1 , MS, ScD ;   Summer K Rankin   2 , PhD ;   Katherine Dowdy   2 , BA ;   Sergey V Blok   2 , PhD ;   Susan J Bright   3 , MPH, DVM ;   Lee Anne M Palmer   3 , MPH, VMD

1 US Food and Drug Administration, Silver Spring, MD, United States

2 Booz Allen Hamilton, McLean, VA, United States

3 US Food and Drug Administration, Rockville, MD, United States

Corresponding Author: