Prostate Cancer Survival Prediction: Integrating Clinical Insights, Genomics and Machine Learning for Precision Care
Year: 2025
Type: article
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.
Source: Cuestiones de Fisioterapia
DOI: 10.48047/z26x8926
Authors: Bhupesh Kumar Gupta, Bhavya Alankar, Harleen Kaur, Parul Agarwal
Institution: Jamia Hamdard
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4408272937