An Investigative Study on Early Diagnosis of Prostate Cancer Using Neuro-Fuzzy Classification System for Pattern Recognition

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Research Article

Publication Title

International Journal of Fuzzy Systems


Prostate cancer is one of the main causes of death among men in the world. In the first stage, the authors have proposed a mathematical modeling for the early detection of prostate cancer using the measurement of prostate-specific antigen (PSA) level in blood, age, and prostate volume (PV) of patients. These are used as input parameters into fuzzy tools and using fuzzy rules we evaluate the risk status as output variable. This paper presents a gradation and staging system of prostate cancer using PSA level in blood of patients and Gleason score which provides a useful platform to physicians in determining the status of the disease. In the second stage, the authors present an investigative study on prostate cancer disease and used the neuro-fuzzy classification system for pattern recognition for earliest possible treatment planning.

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