A machine learning-based nomogram for predicting graft survival in allograft kidney transplant recipients: a 20-year follow-up study
This study constructed a nomogram for predicting the 20-year survival rate of kidney graft after allograft kidney transplantation using six factors, which may help clinicians assess kidney transplant recipients individually and intervene.
Authors
- Lingyan Cao (ORCID: https://orcid.org/0000-0002-9858-4256)
- Tao Liu (ORCID: https://orcid.org/0000-0002-3568-4882)
- WenXing Fan (ORCID: https://orcid.org/0000-0002-5526-6901)
- P. Liu (ORCID: https://orcid.org/0009-0003-1751-2184)
- Yifei Li (ORCID: https://orcid.org/0000-0002-3096-4287)
- Feng Su (ORCID: https://orcid.org/0000-0002-9928-9830)
- Jiamin He
Institutions
- Kunming Medical University (CN)
- First Affiliated Hospital of Kunming Medical University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-04-01
- DOI
- https://doi.org/10.3389/fmed.2025.1556374
- Citations
- 2
- Primary Topic
- Renal Transplantation Outcomes and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 3.97