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
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;
Conference_Titel :
Cloud and Services Computing (ISCOS), 2012 International Symposium on
Conference_Location :
Mangalore
Print_ISBN :
978-1-4673-4854-6
DOI :
10.1109/ISCOS.2012.29