Two machine learning-derived nomogram for predicting the occurrence and severity of acute graft-versus-host disease: a retrospective study based on serum biomarkers
Clinical variables screened through learning algorithm can predict the risk and severity of aGVHD. Our findings may help clinicians develop more personalized and reasonable management strategies.
Authors
- Zhe Yu (ORCID: https://orcid.org/0000-0002-6908-6135)
- Xin Li (ORCID: https://orcid.org/0000-0001-7746-4530)
- Linna Xie (ORCID: https://orcid.org/0000-0003-4163-8994)
- Fang Yuan (ORCID: https://orcid.org/0000-0001-8999-3958)
- Fansheng Kong
- Qiang He
Institutions
- Shandong Tumor Hospital (CN)
- Jinan Military General Hospital (CN)
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Frontiers in Genetics
- Published
- 2024-11-08
- DOI
- https://doi.org/10.3389/fgene.2024.1421980
- Citations
- 1
- Primary Topic
- Hematopoietic Stem Cell Transplantation
- Type
- article
- Field-Weighted Citation Impact
- 0.45
Funders
- National Natural Science Foundation of China
- Chinese Society of Clinical Oncology