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Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28946, first published .
Futuristic medical interface showing patient data, ECG, brain scan, and network analysis.

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study

Peter L Elkin   1, 2, 3 , MD ;   Sarah Mullin   1 , PHO ;   Jack Mardekian   4 , PhD ;   Christopher Crowner   1 , MSc ;   Sylvester Sakilay   1 , MSc ;   Shyamashree Sinha   1 , MSc, MD ;   Gary Brady   4 , DPH ;   Marcia Wright   4 , PharmD ;   Kimberly Nolen   4 , PharmD ;   JoAnn Trainer   4 , PharmD ;   Ross Koppel   1 , PhD ;   Daniel Schlegel   1 , PhD ;   Sashank Kaushik   1 , MD ;   Jane Zhao   1 , MD ;   Buer Song   1 , MD, PhD ;   Edwin Anand   1 , MD

1 Department of Biomedical Informatics, University at Buffalo, Buffalo, NY, United States

2 Bioinformatics Laboratory, Department of Veterans Affairs, VA Western New York Healthcare System, Buffalo, NY, United States

3 School of Engineering, University of Southern Denmark, Odense, Denmark

4 Pfizer, Inc., New York, NY, United States

Corresponding Author:

  • Peter L Elkin, MD
  • Department of Biomedical Informatics
  • University at Buffalo
  • 77 Goodell St
  • Suite 5t40
  • Buffalo, NY 14203
  • United States
  • Phone: 1 5073581341
  • Email: elkinp@buffalo.edu