Prostate Cancer Survival Prediction: Integrating Clinical Insights, Genomics and Machine Learning for Precision Care

Authors

  • Bhupesh Kumar Gupta Department of Computer Science & Engineering School of Engineering Science and Technology Jamia Hamdard, New Delhi, 110062 Author
  • Bhavya Alankar Department of Computer Science & Engineering School of Engineering Science and Technology Jamia Hamdard, New Delhi, 110062 Author
  • Harleen Kaur Department of Computer Science & Engineering School of Engineering Science and Technology Jamia Hamdard, New Delhi, 110062 Author
  • Parul Agarwal Department of Computer Science & Engineering School of Engineering Science and Technology Jamia Hamdard, New Delhi, 110062 Author

DOI:

https://doi.org/10.48047/z26x8926

Keywords:

Machine Learning, Prostate Cancer, Survival, Detection

Abstract

Prostate cancer remains a significant global health challenge among men, necessitating robust survival prediction models to enhance clinical decision-making and improve patient outcomes. While traditional prognostic tools—such as Gleason scores, PSA levels and TNM staging—offer valuable insights, they have limitations in precision, scalability and adaptability across diverse patient populations. 

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References

. American Cancer Society. Cancer Facts & Figures. 2023. [2]. Zhu Y, Yao Z, et al. Epidemiology and genomics of prostate cancer in Asian men. Nat Rev Urol. 2021 May;18(5):282-301. doi: 10.1038/s41585-021-00442-8

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Published

2025-02-20

Issue

Vol. 54 No. 4 (2025): Year 2025, Volume 54, Issue 4

Section

Articles

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How to Cite

Prostate Cancer Survival Prediction: Integrating Clinical Insights, Genomics and Machine Learning for Precision Care (B. . Kumar Gupta, B. . Alankar, H. . Kaur, & P. . Agarwal , Trans.). (2025). Cuestiones De Fisioterapia, 54(4), 826-847. https://doi.org/10.48047/z26x8926