Using Fuzzy Concept Lattice for Intelligent Disease Diagnosis | Zendy

Caifeng Zou | Zendy; Huifang Deng | Zendy

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Using Fuzzy Concept Lattice for Intelligent Disease Diagnosis

Author(s) -

Caifeng Zou,

Huifang Deng

Publication year - 2016

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2016.2638848

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper proposes a novel intelligent disease diagnosis method based on fuzzy concept lattice. Symptoms and the corresponding extents (e.g., frequency, severity, and duration) of each disease can be extracted to form a fuzzy concept lattice. The fuzzy concept lattice of the symptoms and their extents to be diagnosed needs to be constructed to match the fuzzy concept lattice of possible diseases. The similarity between the above two types of concept lattices can be calculated and used to aid for effective diagnosis. Naturally, the disease with the largest similarity is the finding of intelligent diagnosis. In the future, more efficient fuzzy concept lattice construction method and update algorithm will be explored, which are presumed to be very complicated.

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