PRESCO: an online tool for predicting severe pulmonary complications and survival after cancer surgery
We developed and validated machine learning models that accurately predict the occurrence and survival of SPCs in cancer patients after surgery. By deploying the online tool, clinicians can easily access it and utilize its functions to perform personalized risk stratification and guide perioperative decisions in oncology.
Authors
- Ke Luo (ORCID: https://orcid.org/0009-0008-6951-8402)
- Lu Wang (ORCID: https://orcid.org/0000-0003-0441-0747)
- Yunyun Su
Institutions
- Hunan Cancer Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2026-01-07
- DOI
- https://doi.org/10.3389/fonc.2025.1705181
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China