Please use this identifier to cite or link to this item: https://ir.vidyasagar.ac.in/jspui/handle/123456789/945
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dc.contributor.authorDev, Utpalendu
dc.contributor.authorSultana, Abeda
dc.contributor.authorMitra, Nirmal Kanti
dc.date.accessioned2016-12-22T17:44:12Z-
dc.date.available2016-12-22T17:44:12Z-
dc.date.issued2015-12-24
dc.identifier.issn2350-0352
dc.identifier.urihttp://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/945-
dc.description7-18en_US
dc.description.abstractFuzzy set theory has a number of properties that make it suitable for formalizing the uncertain information upon which medical diagnosis and treatment is usually based. Firstly, it allows us to define inexact medical entities as fuzzy sets. Secondly, it provides a linguistic approach with an excellent approximation to texts. Finally, fuzzy logic offers powerful reasoning methods capable of drawing approximate inferences. These facts suggest that fuzzy set theory might be a suitable basis for the development of a computerized diagnosis and treatment- recommendation system. This is borne out by trials performed with the medical expert system CADIAG- 2, which uses fuzzy set theory to formalize medical relationshipsen_US
dc.language.isoenen_US
dc.publisherVidyasagar University , Midnapore , West-Bengal , Indiaen_US
dc.relation.ispartofseriesJournal of Physical Science;Vol. 20 [2015]
dc.subjectPhenomenonen_US
dc.subjectPathophysiologicalen_US
dc.subjectPremiseen_US
dc.subjectLingusticen_US
dc.subjectUltrasonicen_US
dc.subjectPancreasen_US
dc.subjectCarcinomaen_US
dc.subjectLumbaren_US
dc.subjectAlphanumaricen_US
dc.subjectLupus erythematodesen_US
dc.subjectSclerodermiaen_US
dc.titleFuzzy Set Theory in Real-World Knowledge and Medical Diagnosis Processen_US
dc.typeArticleen_US
Appears in Collections:Journal of Physical Sciences Vol.20 [2015]

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