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G. G. Towell, J. W. Shavlik and M. O. Noordwier, “Refinement of Approximate Domain Theories by Knowledge Based-Artificial Neural Network,” Proceedings of the 8th National Conference on Artificial Intelligence, Boston, July 1990, pp. 861-866.

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• TITLE: Role of Knowledge Engineering in the Development of a Hybrid Knowledge Based Medical Information System for Atrial Fibrillation

  AUTHORS: Aankita Kaur, Mansaf Alam

  KEYWORDS: Artificial Intelligence (AI); Decision Making; Knowledge Engineering; Knowledge Base; Mortality; Morbidity; Knowledge Management (KM); Experience Management (EM); Knowledge Base System (KBS); Knowledge Management System (KMS); Atrial Fibrillation (AFib); Knowledge Discovery Techniques (KDT); Medical Information System; Medical Information Based Decision Making; Hybrid Intelligent Medical Information System (HIMIS); Hybrid Knowledge Based System

  JOURNAL NAME: American Journal of Industrial and Business Management, Vol.3 No.1, January 17, 2013

  ABSTRACT: In this paper, we are describing role of knowledge engineering in the development of a hybrid knowledge based medical information system. Knowledge engineering plays important role in development of various technologies such as: expert systems, neural network, artificial intelligence, hybrid intelligent systems, data mining, decision support systems, and knowledge based systems etc. The hybrid medical information system mainly consists of medical information system and medical knowledge base systems. These poly techniques of knowledge engineering when integrated with hybrid techniques of intelligent systems for designing, implementing knowledge bases to deal with medical informational data of Atrial Fibrillation. Atrial Fibrillation is the most common heart rhythm disorder which increases the risk of mortality and morbidity.