Identifying the Severity of Heart Valve Stenosis and Regurgitation Among a Diverse Population Within an Integrated Health Care System: Natural Language Processing Approach
The proposed computerized algorithm could effectively identify heart valve stenosis and regurgitation, as well as the severity of valvular involvement, with significant implications for pharmacoepidemiological studies and outcomes research.
Authors
- Salam Allahwerdy (ORCID: https://orcid.org/0000-0003-2206-8033)
- Darios Getahun (ORCID: https://orcid.org/0000-0003-3610-8841)
- Wansu Chen (ORCID: https://orcid.org/0000-0002-3486-7468)
- Fagen Xie (ORCID: https://orcid.org/0000-0002-1565-0490)
- Benjamin S. Wessler (ORCID: https://orcid.org/0000-0002-8652-1426)
- Ming‐Sum Lee (ORCID: https://orcid.org/0000-0001-6121-6452)
Institutions
- Tufts Medical Center (US)
- Kaiser Permanente (US)
- Los Angeles Medical Center (US)
Publication Details
- Journal
- JMIR Cardio
- Published
- 2024-09-09
- DOI
- https://doi.org/10.2196/60503
- Citations
- 3
- Primary Topic
- Cardiac Valve Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- Kaiser Permanente