An online clustering algorithm predicting model for prostate cancer based on PHI-related variables and PI-RADS in different PSA populations
In conclusion, our clustering model effectively categorizes patients into distinct risk groups with clear visualization and has demonstrated stability and reliability in the validation cohort, potentially aiding in early diagnosis of prostate cancer in clinical practice.
Authors
- Jianbin Bi (ORCID: https://orcid.org/0000-0002-7703-4765)
- Gejun Zhang (ORCID: https://orcid.org/0000-0003-3482-5468)
- Xianlu Zhang
- Jiyuan Hu (ORCID: https://orcid.org/0000-0003-1332-5587)
- Haoxiang Su (ORCID: https://orcid.org/0009-0007-1057-5499)
- Jiayi Ren
- Qi Miao (ORCID: https://orcid.org/0000-0003-3370-9692)
Institutions
- Shandong University (CN)
- First Hospital of China Medical University (CN)
- Shandong Women’s University (CN)
- China Medical University (CN)
Publication Details
- Journal
- Cancer Cell International
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1186/s12935-025-03677-2
- Citations
- 2
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 3.04
Funders
- National Natural Science Foundation of China
- Scientific Research Fund of Liaoning Provincial Education Department