Diagnostic Value of Radiomics Based on Various Diffusion Models in Magnetic Resonance Imaging for Prostate Cancer Risk Stratification
The predictive model constructed from clinical and radiomic features exhibited substantial diagnostic differentiation capabilities for clinically insignificant and significant PCa. The clinical-radiomic model displayed the highest predictive performance, promising significant contributions to future clinical treatment and assessment of PCa.
Authors
- Bing Du (ORCID: https://orcid.org/0000-0003-1603-1613)
- Shaofeng Duan (ORCID: https://orcid.org/0000-0001-9413-7574)
- Yongsheng He (ORCID: https://orcid.org/0000-0001-6352-6286)
- Wuling Wang
- Qiong Chen (ORCID: https://orcid.org/0000-0002-2534-8834)
- Xue Wei (ORCID: https://orcid.org/0000-0001-7539-7485)
- Xuan Qi (ORCID: https://orcid.org/0000-0002-7581-6106)
- Hongkai Yang (ORCID: https://orcid.org/0009-0005-2303-0725)
Institutions
- Wannan Medical College (CN)
- Dahua Hospital (CN)
- Anshan Hospital (CN)
- Anhui University of Technology (CN)
Publication Details
- Journal
- Current Medical Imaging Formerly Current Medical Imaging Reviews
- Published
- 2024-11-08
- DOI
- https://doi.org/10.2174/0115734056341995240906070046
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Wannan Medical College
- Anhui Provincial Key Research and Development Plan