Abstract
Prostate cancer is one of the most commonly diagnosed malignant diseases and second leading cause of death connected with cancer in men. Diagnosis and therapy of prostate cancer involves interpretation of information from variant sources which can help us to make a final decision like level od PSA (prostate specific antigen), prostatic acid phosphatase (PAP), free to total PSA ratio, genomic biomarkers and biopsy complemented with MRI and Gleans score. In prostate cancer, artificial intelligence has been a really good tool in stratification assessment and also in therapy of prostate cancer using diagnosis through biomarkers, MRI and histopathology analysis. This paper presents the development of an artificial neural network (ANN) for diagnosis of prostate cancer based on 4 input parameters. The dataset consisted of 20% healthy control subjects and 80% diseased subjects. The obtained accuracy of the developed ANN indicates its potential for use as aid in diagnosis and prediction of prostate cancer.
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