Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/322257
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dc.date.accessioned2021-04-24T10:20:45Z-
dc.date.available2021-04-24T10:20:45Z-
dc.identifier.urihttp://hdl.handle.net/10603/322257-
dc.description.abstractnewline Lungs cancer detection using Artificial Intelligence technique is becoming one of the most famous research areas. This is due to increase in the death rate due to lungs cancer. The incidence and humanity rate of lung cancer rank first among various cancers across the world. Once diagnosed, lung cancer often reaches the terminal stage quickly, and thus patients lose the best treatment time. X-ray and CT scanning are often used to screen for early lung cancer patients, but the problems of low sensitivities and specificities exist. Researcher is being done to diagnose cancer with miRNA-21but the sensitivity up to 70-80% is achieved. Soft computing can employ a variety of feature extraction, feature optimization and classification techniques on the biomedical images so as to cure the disease at an early stage. This approach of soft computing is in particular well suited to biomedical applications, those that depend on complex proteomic and genomic measurements.
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dc.languageEnglish
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dc.rightsuniversity
dc.titleBioMedical Image Classification For Cancer Detection By Using Feed Forward Back Propagation Neural Network
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dc.creator.researcherPankaj Nanglia
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.description.note
dc.contributor.guideAprana N Mahajan
dc.publisher.placeSolan
dc.publisher.universityMaharaja Agrasen University
dc.publisher.institutionMaharaja Agrasen Institute of Technology
dc.date.registered2015
dc.date.completed2020
dc.date.awarded2020
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dc.format.accompanyingmaterialCD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Maharaja Agrasen Institute of Technology



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