The Medical Signals Acquisition and Management System for Computer-Aid of Prostate Cancer Diagnosis

In this paper the procedure of conditioning and merging the medical signals as the important element of expert system for the diagnosis of prostate cancer (PC) and benign prostatic hyperplasia (BPH) is presented. Patient, who comes to urologist, is an object of measurement and the process of identification should qualify its essential features from doctor's point of view. The conditioning is based on medical expert knowledge. This knowledge is translated into a probabilistic model (the Bayesian network model), which represents knowledge base of the system. The model combines knowledge of experts with the data that is obtained from the questionnaires. The input values of this system are the results of anamnesis and investigations. In this paper we propose also the internet option for data collection to enhance physician's administrative work.