Developing a Knowledge-Based System to Automate the Diagnosis of Allergic Rhinitis

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概要

• 論文の詳細を見る

• This paper studies a knowledge-based system implementation method to realize the preliminary diagnosis of nasal allergy. Constructing the rule base and the case base, respectively based on the knowledge of doctor and the questionnaire of patient at first, and putting the information of the patient for diagnosis into the two bases and scanning the bases, the system can give the suitable diagnosis. The rule-base reasoning and learning (RBRL) algorithm are performed by a neural network at first, and then the case base reasoning (CBR) algorithm is also performed by using fuzzy method. On the other hand, since algorithm of the neural networks can be convertible to that of fuzzy method, it is reasonable to combine the merits of both paradigms, that is, to combine the learning ability of neural network and the easy implementation of fuzzy logic.

• バイオメディカル・ファジィ・システム学会の論文
• 1996-08-08

著者

• Chae Young

  Dept. of Preventive Medicine and public Health, Yonsei University College of Medicine

• Park Mignon

  Dept. of Electronic Engineering, Yonsei University College of Engineering

• Chae Young

  Dept. Of Preventive Medicine And Public Health Yonsei University College Of Medicine

• PARK Kyung

  Computer Science, Hyejeon JuniorCollege

• Park Kyung

  Computer Science Hyejeon Juniorcollege

• Park Mignon

  Dept. Of Electronic Engineering Yonsei University College Of Engineering

• Park Mignon

  Dept. Of Electronic Eng. Yonsei Univ.

関連論文

• 13. A study on the development of a fuzzy-neuro preliminary medical examination system for diagnosing nasal allergy
• Developing a Knowledge-Based System to Automate the Diagnosis of Allergic Rhinitis
• AUTOMATIZING SKIN ALLERGY TEST AND DIAGNOSIS USING FUZZY AND NEURAL NETWORKS
• The State Feedback Control Based on Fuzzy Observer for T-S Fuzzy Systems with Unknown Time-Delay(Systems and Control)

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