• DocumentCode
    342591
  • Title

    Rough sets and reasoning about complications-granular computation in medical reasoning

  • Author

    Tsumoto, Shusaku

  • Author_Institution
    Med. Res. Inst., Tokyo Med. & Dental Univ., Japan
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    795
  • Lastpage
    799
  • Abstract
    One of the most difficult problems in modeling medical reasoning is to model a procedure for diagnosis about complications. In medical contexts, a patient sometimes suffers from several diseases and has complicated symptoms, which makes a differential diagnosis very difficult. For example, in the domain of headache, a patient suffering from migraine, (a vascular disease), may also suffer from muscle contraction headache (a muscular disease). In this case, symptoms specific to vascular diseases will be observed with those specific to muscular ones. Since one of the essential processes in diagnosis of headache is discrimination between vascular and muscular diseases, simple rules will not work to rule out one of the two groups. However, medical experts do not have this problem and conclude both diseases. In this paper, three models for reasoning about complications are introduced and modeled by using characterization and rough set model. This clear representation, suggests that this model should be used by medical experts implicitly
  • Keywords
    inference mechanisms; medical expert systems; rough set theory; differential diagnosis; granular computation; medical reasoning; muscle contraction headache; reasoning; rough sets; Cities and towns; Dentistry; Diseases; Information systems; Medical diagnostic imaging; Muscles; Rough sets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
  • Conference_Location
    New York, NY
  • Print_ISBN
    0-7803-5211-4
  • Type

    conf

  • DOI
    10.1109/NAFIPS.1999.781803
  • Filename
    781803