Published on in Vol 3, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36877, first published .
Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study

Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study

Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study

Aaron Wendelboe   1 , PhD ;   Ibrahim Saber   2 , MD ;   Justin Dvorak   1 , PhD ;   Alys Adamski   3 , PhD ;   Natalie Feland   1 , RN ;   Nimia Reyes   3 , MD ;   Karon Abe   3 , PhD ;   Thomas Ortel   2 , MD, PhD ;   Gary Raskob   1 , PhD

1 Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States

2 Division of Hematology, Department of Medicine, Duke University, Durham, NC, United States

3 Division of Blood Disorders, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, United States

Corresponding Author:

  • Aaron Wendelboe, PhD
  • Department of Biostatistics and Epidemiology
  • Hudson College of Public Health
  • University of Oklahoma Health Sciences Center
  • CHB Room 301
  • 801 NE 13th Street
  • Oklahoma City, OK, 73104
  • United States
  • Phone: 1 405 271 2229 ext 57897
  • Email: Aaron-Wendelboe@ouhsc.edu