Chronic Kidney Disease Prediction System

Authors(3) :-Ammavajjula Sai Tejaswi, Animilla Swapna Deepika, Yaragani Sowmya

Chronic Kidney Disease (CKD) is a very dangerous health problem that has been spreading due to globally due to alterations in lifestyle such as food habits, changes in the atmosphere, etc. So, it is essential to decide any remedies to avoid and predict the disease in an early stage. This paper focuses on predictive analytics architecture to analyze the CKD dataset using feature engineering and classification algorithm. The proposed model incorporates techniques to validate the feasibility of data points used for analysis. The main focus of research work is to analyze the dataset of chronic kidney failure and perform the classification of CKD and Non-CKD cases.

Authors and Affiliations

Ammavajjula Sai Tejaswi
Computer Science and Engineering, GVP College of Engineering for Women, Visakhapatnam, Andhra Pradesh, India
Animilla Swapna Deepika
Computer Science and Engineering, GVP College of Engineering for Women, Visakhapatnam, Andhra Pradesh, India
Yaragani Sowmya
Computer Science and Engineering, GVP College of Engineering for Women, Visakhapatnam, Andhra Pradesh, India

Feature Engineering, Classification Algorithm.

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Publication Details

Published in : Volume 6 | Issue 2 | March-April 2020
Date of Publication : 2020-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 43-47
Manuscript Number : CSEIT206215
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Ammavajjula Sai Tejaswi, Animilla Swapna Deepika, Yaragani Sowmya, "Chronic Kidney Disease Prediction System", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 2, pp.43-47, March-April-2020. Available at doi : https://doi.org/10.32628/CSEIT206215
Journal URL : https://res.ijsrcseit.com/CSEIT206215 Citation Detection and Elimination     |      |          | BibTeX | RIS | CSV

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