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

Machine Learning (1501) Artificial Intelligence (1421) Clinical Information and Decision Making (1434) Electronic Health Records (1068) Decision Support for Health Professionals (1210)

Published on in Vol 9, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17886, first published .
Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis–Treated Patients Using Stacked Generalization: Model Development and Validation Study

Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis–Treated Patients Using Stacked Generalization: Model Development and Validation Study

Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis–Treated Patients Using Stacked Generalization: Model Development and Validation Study

Authors of this article:

Guilan Kong1, 2 Author Orcid Image ;   Jingyi Wu2 Author Orcid Image ;   Hong Chu3 Author Orcid Image ;   Chao Yang3 Author Orcid Image ;   Yu Lin4 Author Orcid Image ;   Ke Lin1 Author Orcid Image ;   Ying Shi5 Author Orcid Image ;   Haibo Wang1, 6 Author Orcid Image ;   Luxia Zhang1, 2, 3 Author Orcid Image
Article Authors Cited by (8) Tweetations (1) Metrics

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  1. Gan F, Chen W, Liu H, Zhong Y. Application of artificial intelligence models for detecting the pterygium that requires surgical treatment based on anterior segment images. Frontiers in Neuroscience 2022;16 View
  2. Bai Q, Tang W. Artificial intelligence in peritoneal dialysis: general overview. Renal Failure 2022;44(1):682 View
  3. Cheng C, Lin W, Liu H, Chen Y, Chiang C, Hung K. Implementation of artificial intelligence Chatbot in peritoneal dialysis nursing care: Experience from a Taiwan medical center. Nephrology 2023;28(12):655 View
  4. Zhang K, Liu C, Zhao H. Meta-analysis of haematocrit and activated partial thromboplastin time as risk factors for unplanned interruptions in patients undergoing continuous renal replacement therapy. The International Journal of Artificial Organs 2023;46(8-9):498 View
  5. Kong G, Wang J, Lin H, Bao B, Friedman C, Zhang L. Transforming Health Care Through a Learning Health System Approach in the Digital Era: Chronic Kidney Disease Management in China. Health Data Science 2023;3 View
  6. Mushtaq M, Mushtaq M, Ali H, Sarwar M, Bokhari S. Artificial intelligence and machine learning in peritoneal dialysis: a systematic review of clinical outcomes and predictive modeling. International Urology and Nephrology 2024;56(12):3857 View
  7. Zhang M, Zheng Y, Maidaiti X, Liang B, Wei Y, Sun F. Integrating Machine Learning into Statistical Methods in Disease Risk Prediction Modeling: A Systematic Review. Health Data Science 2024;4 View
  8. Hsu F, Hwang R, Tsai M, Wang J. Predicting Peritoneal Dialysis Failure Within the Next Three Months Based on Deep Learning and Important Features Analysis. Information 2024;15(12):776 View