Prediction model of gastrointestinal tumor malignancy based on coagulation indicators such as TEG and neural networks
This study found that the R and MA values are independent predictive factors for the malignancy of gastrointestinal tumors. Compared to other coagulation indicators, the TEG five items have better discrimination ability regarding tumor malignancy. The RFCBC model created in this study outperforms other commonly used binary classification methods in predicting the malignancy of gastrointestinal tumors, providing a new model construction method and feasible approach for future coagulation index prediction of gastrointestinal tumor malignancy.
Authors
- Shidong Shen (ORCID: https://orcid.org/0009-0000-0369-021X)
- Fulong Yu (ORCID: https://orcid.org/0000-0002-6100-8300)
- Song Wang (ORCID: https://orcid.org/0000-0002-4476-1915)
- Xianghua Li (ORCID: https://orcid.org/0000-0002-2172-7271)
- Liang Li (ORCID: https://orcid.org/0000-0002-8602-6329)
- Xiaoyu Yu (ORCID: https://orcid.org/0000-0003-0549-9560)
- Zhining Liu (ORCID: https://orcid.org/0000-0002-2723-5999)
- Qiang Hao (ORCID: https://orcid.org/0000-0001-7075-8237)
- Changqi Sun
- Lin Zhang
Institutions
- Wannan Medical College (CN)
- Anhui Medical University (CN)
- Soochow University (CN)
- Second Affiliated Hospital of Anhui Medical University (CN)
- Monash University (AU)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-03-25
- DOI
- https://doi.org/10.3389/fimmu.2025.1507773
- Primary Topic
- Inflammatory Biomarkers in Disease Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00