Machine Learning In Healthcare for Chronic Kidney Disease Prediction
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© 2021 by IJCTT Journal
Volume-69 Issue-7
Year of Publication : 2021
Authors : Pranjali Kasture
DOI :  10.14445/22312803/IJCTT-V69I7P110

How to Cite?

Pranjali Kasture, "Machine Learning In Healthcare for Chronic Kidney Disease Prediction," International Journal of Computer Trends and Technology, vol. 69, no. 7, pp. 70-75, 2021. Crossref, https://doi.org/10.14445/22312803/IJCTT-V69I7P110

Abstract
Chronic Kidney Disease (CKD) is a common yet deadly disease that can be difficult to detect at an early stage as it doesn’t show too many symptoms. The proposed work is to develop and validate predictive models for the progression of CKD. The main outcome of this is to measure kidney failure, defined as the need for dialysis or pre-emptive kidney transplantation. The model will suggest the patient the way to maintain a healthy lifestyle as well as facilitate the doctor to visually represent the risk and severity of the disease and how to go about the future treatment.

Keywords
CKD, GFR, Machine learning, ANN.

Reference

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