Please use this identifier to cite or link to this item: http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/1364
Title: Medical Knowledge and Fuzzy Expert System
Authors: Dev, Utpalendu
Sultana, Abeda
Mitra, Nirmal Kanti
Keywords: Phelonephritis, chills, hematology, diagnosis, Pathology, antecedent, consequent, susceptible, robust, ventilation, respiratory
Mathematics
Issue Date: 24-Dec-2016
Publisher: Vidyasagar University
Series/Report no.: Journal of Physical Sciences;JPS-v21-art7
Abstract: The term medical knowledge is a superimposed concept for the relationships between symptoms and diagnoses a physician may find in books, journals, monographs, but also in practical experience. In the second half of the 20th century medical knowledge was also stored in computer systems. To assist physicians in medical decision- making and attendance medical expert systems have been constructed that use the theory of fuzzy sets, which was founded in 1965 by Zadeh. The present article delineates two specific pathways resulting from a bifurcation in the history of applied fuzzy expert systems in medicine. This bifurcation occurred in the 1970’s in the history of the theory of fuzzy systems, when Zadeh published the “rule of max-mim composition” and other researchers applied this rule in different areas. This was the origin of two research areas : fuzzy relations, introduced by Elie Sanchez in Marseille. Later on both concepts were used to construct medical knowledge-based systems in medicine. We present two Viennese systems representing these concepts: the “fuzzy version” of the Computer-Assisted DIAGnostic System (CADIAG) which was developed at the end of the 1970s, and a fuzzy knowledge-based control system, FuzzyKBWean, which was established as a real-time application based on the use of a Patient Data Management System (PDMS) in the intensive care unit (ICU) in 1996.
URI: http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/1364
ISSN: 2350-0352
Appears in Collections:Journal of Physical Sciences Vol.21 [2016]

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