Artificial intelligence algorithm was used to establish and verify the prediction model of portal hypertension in hepatocellular carcinoma based on clinical parameters and imaging features
The preoperative evaluation showed that increased PVD, higher Child-Pugh score, and increased FIB-4 score were independent risk factors for PHT in patients with HCC. To predict the occurrence of PHT more effectively, we construct a comprehensive prediction model. The model incorporates clinical parameters, radiomic features, and deep learning features. This fusion of multi-modal features enables the model to capture complex information related to PHT more comprehensively, thus achieving high prediction accuracy and practicability.
Authors
- Meifeng Chen (ORCID: https://orcid.org/0000-0002-7170-0843)
- Tianyi Liang (ORCID: https://orcid.org/0000-0002-0126-6850)
- Ketuan Huang
- Qiang Tao (ORCID: https://orcid.org/0000-0002-5731-9560)
- Tao Peng
- Chuangye Han (ORCID: https://orcid.org/0000-0002-7670-4763)
- Shutian Mo (ORCID: https://orcid.org/0000-0001-9385-0757)
- Fenfang Wu (ORCID: https://orcid.org/0000-0003-1134-280X)
- Guangquan Zhang (ORCID: https://orcid.org/0000-0003-3960-0583)
- Yongfei He (ORCID: https://orcid.org/0000-0001-8813-1416)
- Jicai Wang (ORCID: https://orcid.org/0000-0001-7980-4412)
- Xianjie Shi (ORCID: https://orcid.org/0000-0001-7712-2258)
- Qiang Gao (ORCID: https://orcid.org/0000-0001-7860-6692)
- Yuan Liao (ORCID: https://orcid.org/0000-0003-0534-6767)
Institutions
- Guangxi Medical University (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
- Inner Mongolia Medical University (CN)
Publication Details
- Journal
- Journal of Gastrointestinal Oncology
- Published
- 2025-02-01
- DOI
- https://doi.org/10.21037/jgo-2024-931
- Citations
- 4
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 5.42