HFBO-KSELM: Hybrid Flash Butterfly Optimization-based Kernel Softplus Extreme Learning Machine for Classification of Chronic Kidney Disease
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-023-05337-6.pdf
Reference24 articles.
1. Wang W, Chakraborty G, Chakraborty B (2020) Predicting the risk of chronic kidney disease (ckd) using machine learning algorithm. Appl Sci 11(1):202. https://doi.org/10.3390/app11010202
2. Salkar C (2021) A detailed analysis on kidney and heart disease prediction using machine learning. J Comput Nat Sci 1:9–14
3. Ghosh P, Shamrat FJM, Shultana S, Afrin S, Anjum AA, Khan AA (2020) Optimization of prediction method of chronic kidney disease using machine learning algorithm. In: 2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP), pp 1–6. https://doi.org/10.1109/iSAI-NLP51646.2020.9376787
4. Bhaskar N, Suchetha M (2021) A computationally efficient correlational neural network for automated prediction of chronic kidney disease. IRBM 42(4):268–276. https://doi.org/10.1016/j.irbm.2020.07.002
5. Al-Wahsh H, Lam NN, Quinn RR, Ronksley PE, Sood MM, Hemmelgarn B, Tangri N, Ferguson T, Tonelli M, Ravani P, Liu P (2022) Calculated versus measured albumin-creatinine ratio to predict kidney failure and death in people with chronic kidney disease. Kidney Int. https://doi.org/10.1016/j.kint.2022.02.034
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