Low urinary tract symptoms are common, especially in men over 50. In the investigation the InterCriteria Analysis method for analysis data connected with low urinary tract symptoms is used. The data is collected for one-year period in Clinic of urology in the largest hospital in the University Multiprofile Hospital for Active Treatment Burgas, Bulgaria. With the help of the InterCriteria Analysis method, the dependencies between the selected criteria are established, according to which the symptoms of the lower urinary tract are examined. Appropriate criteria are placed at the input of the Deep learning neural network to predict the degree of intravesical prostatic growth. This approach assisted the decision-making process for subsequent treatment.