• DocumentCode
    1599621
  • Title

    Medical Diagnostics Using Cloud Computing with Fuzzy Logic and Uncertainty Factors

  • Author

    Aswin, V. ; Deepak, S.

  • Author_Institution
    Dept. of Inf. Technol., SSN Coll. of Eng., Chennai, India
  • fYear
    2012
  • Firstpage
    107
  • Lastpage
    112
  • Abstract
    Cloud computing being a very effective and enhanced tool puts us to the notion that it can be applied in medical domain to make it useful for the society. Diagnosis of Diabetes can be proven useful by tracking down its symptoms and fuzzification of the classic symptom levels. Compositional rules of inferences are applied to make conclusions about probability of occurrence of the disease. It leads to the chances of getting awareness about diabetes control before health complications. Across the globe every patient has his own unique symptoms which are maintained and retrieved by local hosts via cloud computing. Embedding the mathematical symptom -- disease diagnosis blended with cloud computing leads to results that can be very useful for physicians and medical researchers in the sacrosanct field to make life saving conclusions from the analysis of the database. The software based analysis of symptoms with diseases is carried out according to Encryption Standards to make it more secure avoiding privacy issues.
  • Keywords
    cloud computing; cryptography; diseases; health care; medical computing; patient diagnosis; probability; cloud computing; compositional rules; diabetes; disease diagnosis; encryption standards; fuzzy logic; health complications; mathematical symptom; medical diagnostics; probability; uncertainty factors; Cloud computing; Cryptography; Databases; Diabetes; Diseases; Medical diagnostic imaging; cloud computing; fuzzy logic; medical diabetes; security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud and Services Computing (ISCOS), 2012 International Symposium on
  • Conference_Location
    Mangalore
  • Print_ISBN
    978-1-4673-4854-6
  • Type

    conf

  • DOI
    10.1109/ISCOS.2012.29
  • Filename
    6481245