作者
Hamida Ilyas, Sajid Ali, Mahvish Ponum, Osman Hasan, Muhammad Tahir Mahmood, Mehwish Iftikhar, Mubasher Hussain Malik
发表日期
2021/8/9
期刊
BMC nephrology
卷号
22
期号
1
页码范围
273
出版商
BioMed Central
简介
Background
Chronic Kidney Disease (CKD), i.e., gradual decrease in the renal function spanning over a duration of several months to years without any major symptoms, is a life-threatening disease. It progresses in six stages according to the severity level. It is categorized into various stages based on the Glomerular Filtration Rate (GFR), which in turn utilizes several attributes, like age, sex, race and Serum Creatinine. Among multiple available models for estimating GFR value, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), which is a linear model, has been found to be quite efficient because it allows detecting all CKD stages.
Methods
Early detection and cure of CKD is extremely desirable as it can lead to the prevention of unwanted consequences. Machine learning methods are being extensively advocated for early detection of symptoms and diagnosis of several diseases recently. With the …
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