A Human-centric User Model for Intelligent Healthcare

Making use of IT technologies, various intelligent healthcare systems are designed which facilitate disease diagnosis, health maintenance and real-time monitoring. To detect and prevent the disease intelligently, user modelling of these system focuses on medical-related user data. However a communication gap between patients and doctors is still so large that yielding amounts of medical complains and accidents. This paper proposes a human-centric semantic user model and developed a novel semantic learning and reasoning approach using a combination of rule-based and case-based reasoning techniques to lessen the communication gap between doctors and patients by focusing on the dedicated user model for the purpose of providing assistants for healthcare decision making.