Machine Learning Models for Chronic Renal Disease Prediction
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7820-5_14
Reference26 articles.
1. Debal, D.A., Sitote, T.M.: Chronic kidney disease prediction using machine learning techniques. J Big Data 9, 109 (2022). https://doi.org/10.1186/s40537-022-00657-5
2. Pal, S.: Chronic kidney disease prediction using machine learning techniques. Biomed. Mater. & Devices (2022). https://doi.org/10.1007/s44174-022-00027-y
3. Moturi, S., Rao, S.T., Vemuru, S.: Grey wolf assisted dragonfly-based weighted rule generation for predicting heart disease and breast cancer. Comput. Med. Imaging Graph., 91, (2021). https://doi.org/10.1016/j.compmedimag.2021.101936
4. Kidney disease: The basics. https://www.kidney.org/news/newsroom/factsheets/KidneyDiseaseBasics. Last accessed 2023/5/4
5. Moturi, S., Vemuru, S.,Tirumala Rao, S.N.: Two phase parallel framework for weighted coalesce rule mining: a fast heart disease and breast cancer prediction paradigm. Biomed. Eng.: Appl., Basis Commun., 34(03), (2022). https://doi.org/10.4015/S1016237222500107
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