Early detection of chronic kidney failure

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dc.contributor.author Syed, Aamer
dc.date.accessioned 2019-08-01T11:08:46Z
dc.date.available 2019-08-01T11:08:46Z
dc.date.issued 2019-05
dc.identifier.uri http://www.aiktcdspace.org:8080/jspui/handle/123456789/3205
dc.description.abstract The growing global burden of Non-communicable disease(NCD’s) worldwide, is increasing day by day. The chronic renal failure is a type of NCD. These chronic disease are one of the leading cause of death. It becomes important for our society, to detect and cure it as early as possible. Our system aims to predict the possibility of chronic renal failure, i.e the chances of kidney failure of a patient. Huge amount of patient’s data and their case histories are stored from years and years, and yet not being used. This data can be used to predict, using massive data sets, by categorizing valid and unique patterns in data. We aim to make a system through which people can regularly check the risk to have chronic renal failure. Keywords: CRF(Chronic Renal Failure), NCD(Non Communicable Disease), Massive Data sets, Prediction Algorithms, Machine Learning. en_US
dc.language.iso en en_US
dc.publisher AIKTC en_US
dc.relation.ispartofseries PE0583;
dc.subject Project Report - CO en_US
dc.title Early detection of chronic kidney failure en_US
dc.type Project Report en_US


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