Letter to the editor for the article “A machine learning approach using stone volume to predict stone-free status at ureteroscopy”
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00345-024-05198-5.pdf
Reference6 articles.
1. Vigneswaran G et al (2024) A machine learning approach using stone volume to predict stone-free status at ureteroscopy. World J Urol 42(1):344
2. Manogaran M, Louzazni M (2022) Analysis of Artificial Neural Network: Architecture, Types, and Forecasting Applications Journal of Electrical and Computer Engineering, 2022
3. Kern C, Klausch T, Kreuter F (2019) Tree-based Machine Learning Methods for Survey Research. Surv Res Methods 13(1):73–93
4. Jimin Tan JY, Wu S, Chen G, Zhao J (2021) A critical look at the current train/test split in machine learning. arXiv preprint
5. Su Q et al (2022) Faecal microbiome-based machine learning for multi-class disease diagnosis. Nat Commun 13(1):6818
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