Random forest can accurately predict the development of end-stage renal disease in immunoglobulin a nephropathy patients-Reference-Cited by-同舟云学术

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Random forest can accurately predict the development of end-stage renal disease in immunoglobulin a nephropathy patients

Published:2019-06 Issue:11 Volume:7 Page:234-234
ISSN:2305-5839
Container-title:Annals of Translational Medicine
language:
Short-container-title:Ann. Transl. Med

Author:

Han Xin,Zheng Xiaonan,Wang Ying,Sun Xiaoru,Xiao Yi,Tang Yi,Qin Wei

Publisher

AME Publishing Company

Subject

General Medicine

Cited by 32 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning-based diagnosis and prognosis of IgAN: A systematic review and meta-analysis;Heliyon;2024-06

2. Personalized decision support system for tailoring IgA nephropathy treatment strategies;European Journal of Internal Medicine;2024-06

3. Privacy-preserving predictive modeling for early detection of chronic kidney disease;Network Modeling Analysis in Health Informatics and Bioinformatics;2024-04-06

4. Application of Machine Learning in Chronic Kidney Disease: Current Status and Future Prospects;Biomedicines;2024-03-03

5. Refractory IgA Nephropathy: A Challenge for Future Nephrologists;Medicina;2024-02-05

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