Clinical value of a radiomics model based on machine learning for the prediction of prostate cancer
Models based on machine learning comprising radiomic features and clinical indicators showed good predictive efficiency for PCa and csPCa. These findings demonstrate the utility of radiomic models for clinical decision-making.
Authors
- Shaoqin Jiang (ORCID: https://orcid.org/0000-0001-5471-8980)
- Mengqiang Li (ORCID: https://orcid.org/0000-0002-0305-3357)
- Yue Cheng Xu (ORCID: https://orcid.org/0000-0003-2755-4719)
- Ruiling Dou
- Zhenlin Chen (ORCID: https://orcid.org/0000-0003-2100-1363)
- Zhihao Li (ORCID: https://orcid.org/0000-0002-6009-7903)
- Shaoshan Lin
- Zhang-Cheng Huang
Institutions
- Fujian University of Traditional Chinese Medicine (CN)
- Fujian Medical University (CN)
- Second Military Medical University (CN)
- Changhai Hospital (CN)
- Union Hospital (CN)
Publication Details
- Journal
- Journal of International Medical Research
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1177/03000605241275338
- Citations
- 5
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.09