Prediction of high-risk prostate cancer based on the habitat features of biparametric magnetic resonance and the omics features of contrast-enhanced ultrasound
The combination of the habitat features of bp-MRI and the omics features of CEUS can help predict high-risk PCa.
Authors
- Xinhong Liao
- Qun Huang (ORCID: https://orcid.org/0000-0003-1898-0601)
- Fangyi Huang
- Yong Gao (ORCID: https://orcid.org/0000-0002-2468-9282)
Institutions
- First Affiliated Hospital of GuangXi Medical University (CN)
Publication Details
- Journal
- Heliyon
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e37955
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangxi Province