Machine Learning Prediction Model of Waitlist Outcomes in Patients with Primary Sclerosing Cholangitis
Our RSF model offers more accurate waitlist outcome prediction in PSC. The significant performance improvement with the inclusion of PSC-specific variables highlights the importance of disease-specific variables for predicting trajectories of clinically distinct presentations.
Authors
- Rahul Krishnan
- Elmar Jaeckel (ORCID: https://orcid.org/0000-0003-4108-7192)
- Gideon M. Hirschfield (ORCID: https://orcid.org/0000-0002-6736-2255)
- Maryam Naghibzadeh (ORCID: https://orcid.org/0000-0002-1780-7113)
- Mamatha Bhat (ORCID: https://orcid.org/0000-0003-1960-8449)
- Nazia Selzner (ORCID: https://orcid.org/0000-0002-9435-2597)
- Cynthia Tsien (ORCID: https://orcid.org/0000-0002-9807-3843)
- Mary Vyas
- Yingji Sun (ORCID: https://orcid.org/0009-0007-5238-5722)
- Leslie Lilly
- Arya Rahmani
Institutions
- University Health Network (CA)
- University of Toronto (CA)
Publication Details
- Journal
- Transplantation Direct
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1097/txd.0000000000001774
- Citations
- 1
- Primary Topic
- Liver Diseases and Immunity
- Type
- article
- Field-Weighted Citation Impact
- 1.32