Abstract
The diagnosis of prostate cancer relies on various commonly used criteria, including PSA, fPSA, PV and AGE. This study explores the application of the soft set model to analyze these parameters and determine their relationships, aiming to identify the most influential parameter for the diagnosis of prostate cancer. Through the analysis of these parameters, the dominant parameter is determined, enabling healthcare professionals to prioritize and focus on the most significant factor when assessing the likelihood of prostate cancer in patients. The findings of this research provide valuable insights for medical practitioners to make informed decisions in the management of prostate cancer.
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