Applying diagnosis support systems in electronic health records to identify wild-type transthyretin amyloid cardiomyopathy risk

Authors

Connor Willis, University of Utah
Alexandre H Watanabe, University of Utah
Justin Hughes, MedStar Health Research Institute
Kimberly Nolen, Pfizer
Jason O'Meara, Pfizer
Alexander Schepart, Pfizer
Marianna Bruno, Pfizer
Joseph Biskupiak, University of Utah
Kensaku Kawamoto, University of Utah
Nawar Shara, MedStar Health Research Institute
Thomas Kannampallil, Washington University School of Medicine in St. Louis

Journal

Future Cardiology

Publication Date

5-1-2022

Volume

18

Issue

5

First Page

367

Last Page

376

Document Type

Open Access Publication

DOI

10.2217/fca-2021-0122

Rights and Permissions

Willis C, Watanabe AH, Hughes J, Nolen K, O'Meara J, Schepart A, Bruno M, Biskupiak J, Kawamoto K, Shara N, Kannampallil T. Applying diagnosis support systems in electronic health records to identify wild-type transthyretin amyloid cardiomyopathy risk. Future Cardiol. 2022 May;18(5):367-376. doi: 10.2217/fca-2021-0122. This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. For full bibliographic citation, please refer to the version available at www.futuremedicine.com.

Recommended Citation

Willis, Connor; Watanabe, Alexandre H; Hughes, Justin; Nolen, Kimberly; O'Meara, Jason; Schepart, Alexander; Bruno, Marianna; Biskupiak, Joseph; Kawamoto, Kensaku; Shara, Nawar; and Kannampallil, Thomas, "Applying diagnosis support systems in electronic health records to identify wild-type transthyretin amyloid cardiomyopathy risk." Future Cardiology. 18, 5. 367 - 376. (2022).
https://digitalcommons.wustl.edu/oa_4/410