Performance Evaluation and Comparative Analysis of Machine Learning Techniques to Predict the Chronic Kidney Disease
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8479-4_35
Reference21 articles.
1. Revathy S, Bharathi B, Jeyanthi P, Ramesh M (2019) Chronic kidney disease prediction using machine learning models. Int J Eng Adv Technol 9(1):6364–6367. https://doi.org/10.35940/ijeat.A2213.109119
2. Khalid H, Khan A, Zahid Khan M, Mehmood G, Shuaib Qureshi M (2023) Machine learning hybrid model for the prediction of chronic kidney disease. Comput Intell Neurosci 9266889. https://doi.org/10.1155/2023/9266889
3. Kalantar-Zadeh K, Jafar TH, Nitsch D, Neuen BL, Perkovic V (2021) Chronic kidney disease. The Lancet 398(10302):786–802. https://doi.org/10.1016/S0140-6736(21)00519-5
4. Qin J, Chen L, Liu Y, Liu C, Feng C, Chen B (2020) A machine learning methodology for diagnosing chronic kidney disease. IEEE Access 8:20991–21002. https://doi.org/10.1109/ACCESS.2019.2963053
5. Kovesdy CP (2022) Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl 12(1):7–11. https://doi.org/10.1016/j.kisu.2021.11.003
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