Design of an IT System for Hepatocellular Carcinoma

Abstract

During the development of an Information Technology System for Predictive, Preventive and Personalized Medicine (ITS-PM) for hepatocellular cancer (HCC) a wide number of variables or Information Entities (IEs) will be identified, and their relative value will be determined. These include factors reflecting: (1) clinical assessment of the patient including functional status, liver function, degree of cirrhosis, and comorbidities; (2) tumor biology, at a molecular, genetic, and anatomic level; (3) tumor burden and individual patient response; and, (4) medical and operative treatments and their outcomes. Beyond the development of database systems, our goals include the development of a realistic, plausible approach to the development of Digital Patient Models (DPMs) and Model Guided Therapy (MGT). These will be based on a complex of database and knowledge management systems capable of data storage, data mining, data analysis, and decision support. In this Chapter we have outlined the required structure and function of an ITS-PM that would be suitable for these tasks. The database structure, composed of three layers, has been described and sample entity-relationship diagrams populated from the clinical material described in Chaps. 3–11 have been presented. Methodologies are proposed that include Multi-Entity Bayesian Networks (MEBN), Reference Model for Open Distributed Processing (RM-ODP), and Service-Oriented Architecture (SOA), which can be considered a subset of RM-ODP. These can provide the comprehensive techniques and structures to be employed to successfully meet the requirements for an ITS-PM.