Diagnosis Values of Back Propagation Neural Network Integrating Age, Transrectal Ultrasound Characteristics and Serum PSA for Prostate Cancer

Objective To explore the diagnosis value of back propagation (BP) neural network integrating age, transrectal ultrasound characteristics and serum prostate specific antigen (PSA) for prostate cancer. Methods The data of age, PSA, and transrectal ultrasound characteristics were collected from 941 patients who received color doppler transrectal ultrasound scan and systemic biopsies of prostates. A prostate cancer diagnosis system of BP neural network with age, transrectal ultrasound characteristics and serum PSA was developed in MATLAB software, and its diagnostic value for prostate cancer was analyzed based on the pathological results of prostatic biopsy. Results The biopsy results confirmed 358 cases of prostate cancer (38.04%) and 583 cases noncancerous prostate diseases (61.96%). The sensitivity, specificity, accuracy, positive value and negative predictive value of BP neural networks for prostate cancer diagnosis were 78.57%, 92.94%, 87.23%, 88.00% and 86.81% respectively. Conclusion Back propagation neural network with age, transrectal ultrasound characteristics and PSA shows good diagnosis value for prostate cancer.