Early detection of chronic kidney failure
| 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.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.identifier.uri | http://www.aiktcdspace.org:8080/jspui/handle/123456789/3205 | |
| 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 |