Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41142, first published .
Machine Learning–Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study

Machine Learning–Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study

Machine Learning–Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study

Journals

  1. Nagy M, Onder A, Rosen D, Mullett C, Morca A, Baloglu O. Predicting pediatric cardiac surgery-associated acute kidney injury using machine learning. Pediatric Nephrology 2024;39(4):1263 View
  2. Dong Z, Liang X. A glimpse of recent advances in the research of acute kidney injury. Medicine Advances 2023;1(2):158 View
  3. Wang L, Duan S, Yan P, Luo X, Zhang N. Utilization of interpretable machine learning model to forecast the risk of major adverse kidney events in elderly patients in critical care. Renal Failure 2023;45(1) View
  4. Liu F, Yao J, Liu C, Shou S. Construction and validation of machine learning models for sepsis prediction in patients with acute pancreatitis. BMC Surgery 2023;23(1) View
  5. Yang X, Qiu H, Wang L, Wang X. Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study. Journal of Medical Internet Research 2023;25:e44417 View
  6. Jia T, Xu K, Bai Y, Lv M, Shan L, Li W, Zhang X, Li Z, Wang Z, Zhao X, Li M, Zhang Y. Machine-learning predictions for acute kidney injuries after coronary artery bypass grafting: a real-life muticenter retrospective cohort study. BMC Medical Informatics and Decision Making 2023;23(1) View
  7. Gao Y, Wang C, Dong W, Li B, Wang J, Li J, Tian Y, Liu J, Wang Y. An Explainable Machine Learning Model to Predict Acute Kidney Injury After Cardiac Surgery: A Retrospective Cohort Study. Clinical Epidemiology 2023;Volume 15:1145 View
  8. Nedadur R, Bhatt N, Chung J, Chu M, Ouzounian M, Wang B. Machine learning and decision making in aortic arch repair. The Journal of Thoracic and Cardiovascular Surgery 2025;169(1):59 View
  9. Shi S, Xiong C, Bie D, Li Y, Wang J. Development and Validation of a Nomogram for Predicting Acute Kidney Injury in Pediatric Patients Undergoing Cardiac Surgery. Pediatric Cardiology 2025;46(2):305 View
  10. Zhang W, Chang Y, Cheng C, Zhao X, Tang X, Lu F, Hu Y, Yang C, Ding Y, Shi R. A machine learning model for predicting acute kidney injury secondary to severe acute pancreatitis. Chinese Medical Journal 2024;137(5):619 View
  11. Chang T, Chen Y, Lu H, Wu J, Mak K, Yu C. Specific patterns and potential risk factors to predict 3-year risk of death among non-cancer patients with advanced chronic kidney disease by machine learning. Medicine 2024;103(7):e37112 View
  12. Lu X, Chen Y, Zhang G, Zeng X, Lai L, Qu C. Application of interpretable machine learning algorithms to predict acute kidney injury in patients with cerebral infarction in ICU. Journal of Stroke and Cerebrovascular Diseases 2024;33(7):107729 View
  13. Bie D, Li Y, Wang H, Liu Q, Dou D, Jia Y, Yuan S, Li Q, Wang J, Yan F. Relationship between intra-operative urine output and postoperative acute kidney injury in paediatric cardiac surgery. European Journal of Anaesthesiology 2024;41(12):881 View
  14. Xu L, Jiang S, Li C, Gao X, Guan C, Li T, Zhang N, Gao S, Wang X, Wang Y, Che L, Xu Y. Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach. Renal Failure 2024;46(2) View
  15. Ma M, Chen C, Chen D, Zhang H, Du X, Sun Q, Fan L, Kong H, Chen X, Cao C, Wan X. A Machine Learning–Based Prediction Model for Acute Kidney Injury in Patients With Community-Acquired Pneumonia: Multicenter Validation Study. Journal of Medical Internet Research 2024;26:e51255 View
  16. Ocampo Osorio F, Alzate-Ricaurte S, Mejia Vallecilla T, Cruz-Suarez G. The anesthesiologist’s guide to critically assessing machine learning research: a narrative review. BMC Anesthesiology 2024;24(1) View
  17. Luo X, Zhang N, Deng Y, Wang H, Kang Y, Duan S. Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning–Based Model Development and Validation Study. Journal of Medical Internet Research 2025;27:e52786 View
  18. Ye M, Liu C, Yang D, Gao H. Development and validation of a risk prediction model for acute kidney injury in coronary artery disease. BMC Cardiovascular Disorders 2025;25(1) View