Interpretable machine learning model to predict 90-day radiographically confirmed pneumonia after chemotherapy initiation in non-Hodgkin lymphoma: development and internal validation of a single-center cohort
The interpretable GBM model demonstrated promising discrimination and calibration on an internal hold-out test set; however, clinical deployment requires temporal and multicenter external validation (as well as prospective assessment with potential recalibration). The accompanying web calculator is a research-only prototype and is not intended for clinical decision-making until such validation is completed.
Authors
- Xiangmin Tong (ORCID: https://orcid.org/0000-0002-4175-0321)
- Lingling Kong (ORCID: https://orcid.org/0000-0002-6266-9741)
- Panruo Jiang
- Lei Wang (ORCID: https://orcid.org/0000-0003-0781-7198)
- Zhanna Zhang
- Manqi Su
- Gongqiang Wu
Institutions
- Wenzhou Medical University (CN)
- Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-09-22
- DOI
- https://doi.org/10.3389/fmed.2025.1674896
- Primary Topic
- Lung Cancer Treatments and Mutations
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Jinhua Science and Technology Bureau
- Medical Science and Technology Project of Zhejiang Province
- Science and Technology Program of Zhejiang Province