This paper is in the following e-collection/theme issue:

Machine Learning (1952) Artificial Intelligence (1983) Advanced Data Analytics in eHealth (191) Big Data (303) Decision Support for Health Professionals (1460) Electronic Health Records (1267) Nephrology/Renal Disorders (90)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52837, first published .
Personalized Prediction of Long-Term Renal Function Prognosis Following Nephrectomy Using Interpretable Machine Learning Algorithms: Case-Control Study

Personalized Prediction of Long-Term Renal Function Prognosis Following Nephrectomy Using Interpretable Machine Learning Algorithms: Case-Control Study

Personalized Prediction of Long-Term Renal Function Prognosis Following Nephrectomy Using Interpretable Machine Learning Algorithms: Case-Control Study

Authors of this article:

Lingyu Xu1 Author Orcid Image ;   Chenyu Li1, 2 Author Orcid Image ;   Shuang Gao3 Author Orcid Image ;   Long Zhao1 Author Orcid Image ;   Chen Guan1 Author Orcid Image ;   Xuefei Shen1 Author Orcid Image ;   Zhihui Zhu4 Author Orcid Image ;   Cheng Guo5 Author Orcid Image ;   Liwei Zhang6 Author Orcid Image ;   Chengyu Yang1 Author Orcid Image ;   Quandong Bu1 Author Orcid Image ;   Bin Zhou1 Author Orcid Image ;   Yan Xu1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Li Y, Xiao M, Li Y, Lv L, Zhang S, Liu Y, Zhang J. Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation. JMIR Medical Informatics 2025;13:e72349 View
  2. Ianiotescu S, Gingu C, Iordache A, Preda A, Salloum O, Balescu I, Bacalbasa N, Sinescu I. Optimizing outcomes of partial nephrectomy in patients with tumors in solitary kidneys: a non-systematic review. Journal of Medicine and Life 2025;18(4):270 View