Early Discovery of Chronic Kidney Disease by Attributing Missing Values

Chronic kidney disease is a common complaint that mainly affects the elderly. This leads to a more dangerous stage in humans where the kidneys stop working within a few days. However, many people who complain about their habitual behavior can live a long life. But, does not work out for all. There i...

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Bibliographic Details
Published in2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) pp. 1561 - 1565
Main Authors Madhavi, S., J, Pathmanaban, S, Sangeetha, K S, Riya
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.04.2022
Subjects
Data transfer
Habitual order complaint
Informatics
integrated model
Kidney
KNN insinuation
Machine learning algorithms
machine literacy
Older adults
Prognostics and health management
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Summary:Chronic kidney disease is a common complaint that mainly affects the elderly. This leads to a more dangerous stage in humans where the kidneys stop working within a few days. However, many people who complain about their habitual behavior can live a long life. But, does not work out for all. There is no early prognosis for detecting the early symptoms of chronic kidney failure. Chronic kidney disease can only be diagnosed when tests show high levels of the substance in the body's urine and blood, indicating that the kidneys are not functioning properly. Detecting the disease early can treat CKD, which may not lead to higher stages such as kidney failure and often death. There are too many possibilities of missing values while generating test results. Therefore, numerous missing values during medical testing are calculated by KNN imputation with machine learning algorithms.
DOI:10.1109/ICOEI53556.2022.9777189