Standardizing phenotypic algorithms for the classification of degenerative rotator cuff tear from electronic health record systems
These algorithms represent an improvement over prior DCT phenotyping strategies and can be useful in large-scale EHR studies.
Authors
- Anoop S. Chandrashekar (ORCID: https://orcid.org/0000-0003-2079-3303)
- Lance E. LeClere (ORCID: https://orcid.org/0000-0002-4154-9900)
- Simone Herzberg (ORCID: https://orcid.org/0000-0001-9971-9821)
- Ayush Giri (ORCID: https://orcid.org/0000-0002-7786-4670)
- Nitin B. Jain (ORCID: https://orcid.org/0000-0002-4362-8522)
- Srushti Gangireddy
- Henry H. Ong (ORCID: https://orcid.org/0000-0001-7960-7363)
- Katherine E. Hartmann (ORCID: https://orcid.org/0000-0002-7051-8185)
- Wanqing Wen (ORCID: https://orcid.org/0000-0002-3004-5168)
- Wei-Qi Wei
- Nelly-Estefanie Garduno-Rapp
Institutions
- University of Kentucky (US)
- Vanderbilt University (US)
- University of Michigan (US)
- The University of Texas Southwestern Medical Center (US)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-02-07
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf014
- Primary Topic
- Shoulder Injury and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Institute of Arthritis and Musculoskeletal and Skin Diseases