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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: June 2024

Volume 9 | Issue 6

Impact factor: 8.15

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Paper Title: Chronic Kidney Disease Prediction with Ensemble Approaches
Unique Id: IJSDR2405054
Published In: Volume 9 Issue 5, May-2024
Abstract: Chronic kidney disease (CKD) represents a critical public health challenge globally, demanding early detection and intervention to mitigate its adverse effects. This initiative presents a comprehensive approach to developing a robust machine learning model for the early prediction of CKD, leveraging the power of random forest, gradient boosting, and logistic regression algorithms. By analysing extensive CKD datasets encompassing clinical and demographic attributes, advanced techniques in ensemble learning are employed to enhance diagnostic accuracy. Comparative analyses against individual classifiers demonstrate the superiority of the ensemble approach in CKD prediction. Moreover, rigorous validation techniques ensure the model's robustness and generalization across diverse patient populations and clinical scenarios. The proposed ensemble machine learning framework represents a significant advancement in CKD prediction, offering enhanced diagnostic accuracy and early intervention opportunities. By leveraging the strengths of multiple algorithms and advanced ensemble techniques, the model provides clinicians with a reliable tool for proactive CKD management.
Keywords: CKD, Accuracy, Ensemble Approach
Cite Article: "Chronic Kidney Disease Prediction with Ensemble Approaches", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 5, page no.379 - 381, May-2024, Available :http://www.ijsdr.org/papers/IJSDR2405054.pdf
Downloads: 000342234
Publication Details: Published Paper ID: IJSDR2405054
Registration ID:211211
Published In: Volume 9 Issue 5, May-2024
DOI (Digital Object Identifier):
Page No: 379 - 381
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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