Comparison of multiple machine learning models for predicting prognosis of pancreatic ductal adenocarcinoma based on contrast-enhanced CT radiomics and clinical features
A combined model of clinical features and AP+VP-Radscore screened using multiple ML algorithms has an excellent ability to predict the prognosis of PDAC and may provide a noninvasive and effective method for clinical decision-making.
Authors
- Yue Huang (ORCID: https://orcid.org/0000-0002-0864-8990)
- Guozhong Liu (ORCID: https://orcid.org/0000-0002-9887-4704)
- Qingzhu Ding
- Shangeng Weng (ORCID: https://orcid.org/0000-0001-8802-6616)
- Xiang Zhang (ORCID: https://orcid.org/0000-0002-5234-9410)
- Han Zhang (ORCID: https://orcid.org/0000-0003-2810-5018)
- Dehua Chen (ORCID: https://orcid.org/0000-0002-1779-8026)
Institutions
- Fujian Medical University (CN)
- First Affiliated Hospital of Fujian Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2024-11-13
- DOI
- https://doi.org/10.3389/fonc.2024.1419297
- Citations
- 6
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 1.70