A STUDY ON BACKPROPAGATION NEURAL NET AND FUZZY INFERENCE SYSTEM BASED MEDICAL DIAGNOSIS AND PERFORMANCE PREDICTION

dc.contributor.guideS. LOURDU MARIAN
dc.coverage.spatial
dc.creator.researcherA. ANTHONISAN
dc.date.accessioned2017-09-01T06:13:02Z
dc.date.available2017-09-01T06:13:02Z
dc.date.awarded
dc.date.completed2013
dc.date.registered11.01.2005
dc.description.abstractquotRecent advances in the field of intelligent systems equipped with Artificial newlineIntelligence techniques called Soft Computing (SC) paved the way to solve complex newlineproblems in human like fashion. SC enables to build flexible information newlineprocessing system capable of handling real life ambiguous situations, and especially newlinein medical diagnosis. It aimed to exploit the tolerance for imprecision, uncertainty, newlineapproximate reasoning and partial truth in order to achieve effective treatment. newlineTheir potential to exploit meaningful relationship set in a data set can be used to newlinediagnosis, treatment and predication of the outcome in many clinical scenarios. newlineAmong the large number of computational techniques used, SC which incorporates newlineNeural Networks, evolutionary computing, Fuzzy Logic and Genetic Algorithms newlineprovides unmatched utility because of its demonstrated strength in handling newlineimprecise information and providing novel solutions to complex problems. newlineThe survey made by Indian Union Health Ministry, reveals that nearly 6.3 % newlineof the population in India suffering from progressive and acute hearing loss. And newlinecurrently the number of hearing impaired in India as 4.482 million people (Source: newlineJaved Abidi Secretary-General Peoples International in India). This research newlinefocuses on intelligent agent to support decision making process in diagnosis of newlineHearing Impairments problems, which especially prevailing in India. Acquiring newlinedata from multiple patients and training the neural net may refine the process of newlinediagnosis and make physicians to make prompt decision.quot newline newline
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/170907
dc.languageEnglish
dc.publisher.institutionDepartment of Computer Application
dc.publisher.placeChennai
dc.publisher.universityBharath University
dc.relation
dc.rightsself
dc.source.universityUniversity
dc.titleA STUDY ON BACKPROPAGATION NEURAL NET AND FUZZY INFERENCE SYSTEM BASED MEDICAL DIAGNOSIS AND PERFORMANCE PREDICTION
dc.title.alternative
dc.type.degreePh.D.

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