• Title/Summary/Keyword: CLINAID

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Investigation of the Reliability of Knowledge Source in CLINAID using Fuzzy Relational Method (Fuzzy Relational Method를 이용한 CLINAID의 Knowledge Source 신뢰성 조사)

  • Noe, Chan-Sook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.2
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    • pp.222-230
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    • 2003
  • Once the medical knowledge-based system has been developed, it is essential to investigate the knowledge sources of the system because knowledge sources can affect the performance of the system in great deal. This paper presents the method and the results of the reliability test done on the medical knowledge-based system CLINAID. A knowledge source tested is Cardiovascular body system data used in CLINAID. The reliability test will be done by investigating structural relationships revealed by fuzzy relational method between the components of the knowledge sources of individual body systems using syndromes as its main component. These partitions are going to be compared with the syndromes elicited from the medical experts. This paper also reports the outcome of the computations using 7 implication operators performed on Cardiovascular body system data.

Comparative Study on the Selection Algorithm of CLINAID using Fuzzy Relational Products

  • Noe, Chan-Sook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.6
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    • pp.849-855
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    • 2008
  • The Diagnostic Unit of CLINAID can infer working diagnoses for general diseases from the information provided by a user. This user-provided information in the form of signs and symptoms, however, is usually not sufficient to make a final decision on a working diagnosis. In order for the Diagnostic Unit to reach a diagnostic conclusion, it needs to select suitable clinical investigations for the patients. Because different investigations can be selected for the same patient, we need a process that can optimize the selection procedure employed by the Diagnostic Unit. This process, called a selection algorithm, must work with the fuzzy relational method because CLINAID uses fuzzy relational structures extensively for its knowledge bases and inference mechanism. In this paper we present steps of the selection algorithm along with simulation results on this algorithm using fuzzy relational products, both harsh product and mean product. The computation results of applying several different fuzzy implication operators are compared and analyzed.