Socially interactive CDSS for u-life care

  • Authors:
  • Iram Fatima;Muhammad Fahim;Donghai Guan;Young-Koo Lee;Sungyoung Lee

  • Affiliations:
  • Kyung Hee University, Korea;Kyung Hee University, Korea;Kyung Hee University, Korea;Kyung Hee University, Korea;Kyung Hee University, Korea

  • Venue:
  • Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
  • Year:
  • 2011

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Abstract

Clinical decision support system (CDSS) is an interactive decision support system computer software, which is designed to assist physicians and other health professionals with decision making tasks, such as determining diagnosis of patient data, disease prevention, and alerting adverse drug events. It links health observations with health knowledge to influence health choices by clinicians for improved health care. Different from conventional CDSSs which focus on diagnosis assistance, the focus of our CDSS is to provide recommendations and healthcare services for chronic disease patients by long term monitoring. To make our CDSS more intelligent, it induces the patients to interact with the system. By continuously learning and digesting patients' experience and knowledge, the knowledge base of our CDSS is self-evolutionary and dynamically enhanced. We mainly develop two modules to achieve the function of social interaction. Firstly, Knowledge Authority Module (KAM) is developed which is capable of manipulating and preprocessing social data. Secondly, to support self-evolutionary and dynamical learning, we designed the rough set based inference engine. Through social interaction, the patients can get continuous relevant medical recommendations from the system, so they can get a chance to improve their health conditions which in turns keeping on their quality of life.