Computational Phenomapping of Randomized Clinical Trial Participants to Enable Assessment of Their Real-World Representativeness and Personalized Inference
This novel multidimensional metric evaluates the real-world representativeness of RCT participants against corresponding patients in the EHR, enabling the evaluation of an RCT's implication for real-world patients.
Authors
- Rohan Khera (ORCID: https://orcid.org/0000-0001-9467-6199)
- Marc A. Suchard (ORCID: https://orcid.org/0000-0001-9818-479X)
- Lovedeep Singh Dhingra (ORCID: https://orcid.org/0000-0002-5664-4126)
- Rahul Jayaram (ORCID: https://orcid.org/0000-0002-7991-4264)
- Arya Aminorroaya (ORCID: https://orcid.org/0000-0003-3197-2657)
- Phyllis Thangaraj (ORCID: https://orcid.org/0000-0003-3968-1563)
- Evangelos K. Oikonomou (ORCID: https://orcid.org/0000-0003-4362-0720)
Institutions
- Yale New Haven Hospital (US)
- University of California, Los Angeles (US)
- Yale University (US)
- Yale New Haven Health System (US)
Publication Details
- Journal
- Circulation Cardiovascular Quality and Outcomes
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1161/circoutcomes.124.011306
- Citations
- 2
- Primary Topic
- Heart Failure Treatment and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.78