CD-KES: An Ontology Based Knowledge Education System for Patients with Chronic Diseases and Its Constructing Approach.

Journal: Studies in health technology and informatics
Published Date: Jan 1, 2017

Abstract

Patients' participation plays a crucial role in the management of chronic diseases. Educating patients about their diseases allows patients to self-regulate their daily health conditions more reasonably and effectively. This study focuses on an informative way to develop daily education and guidance among patients. We provide a systematic approach to establish, process, and present the knowledge map of chronic diseases. An ontology technique is used to model clinical knowledge and rules. Rule-based inference service is constructed based on the RETE reasoning algorithm. Several considerations in semantic visualization and interaction are listed as recommendations. A prototype of Chronic Disease Knowledge Education System (CD-KES) based on this approach has been built for diabetes mellitus. With the prototype, comparative evaluations for system performances in knowledge querying and browsing are taken. The results shows the system can help patients to more easily understand medical knowledge and avoid potential negative consequences.

Authors

  • Chengkai Wu
    Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou Zhejiang Province, China.
  • Ling Gou
    Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou Zhejiang Province, China.
  • Yu Wang
    Clinical and Technical Support, Philips Healthcare, Shanghai, China.
  • Yong Shang
    Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou Zhejiang Province, China.
  • Yu Tian
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Jing-Song Li
    Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou Zhejiang Province, China.

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