An online clustering algorithm predicting model for prostate cancer based on PHI-related variables and PI-RADS in different PSA populations-Reference-Cited by-同舟云学术

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An online clustering algorithm predicting model for prostate cancer based on PHI-related variables and PI-RADS in different PSA populations

Published:2025-02-13 Issue:1 Volume:25 Page:
ISSN:1475-2867
Container-title:Cancer Cell International
language:en
Short-container-title:Cancer Cell Int

Author:

Hu Jiyuan,Miao Qi,Ren Jiayi,Su Hongbo,Zhang Xianlu,Bi Jianbin,Zhang Gejun

Funder

Scientific Research Fund of Liaoning Provincial Education Department

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1186/s12935-025-03677-2.pdf

Reference28 articles.

1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7–33.

2. Schroder FH, Hugosson J, Roobol MJ, Tammela TL, Zappa M, Nelen V, et al. Screening and prostate cancer mortality: results of the European randomised study of screening for prostate cancer (ERSPC) at 13 years of follow-up. Lancet. 2014;384(9959):2027–35.

3. Gronberg H, Adolfsson J, Aly M, Nordstrom T, Wiklund P, Brandberg Y, et al. Prostate cancer screening in men aged 50–69 years (STHLM3): a prospective population-based diagnostic study. Lancet Oncol. 2015;16(16):1667–76.

4. Catalona WJ, Smith DS, Ratliff TL, Dodds KM, Coplen DE, Yuan JJ, et al. Measurement of prostate-specific antigen in serum as a screening test for prostate cancer. N Engl J Med. 1991;324(17):1156–61.

5. Catalona WJ, Partin AW, Slawin KM, Brawer MK, Flanigan RC, Patel A, et al. Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial. JAMA. 1998;279(19):1542–7.

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