Machine learning in solid organ transplantation: Charting the evolving landscape

Table 5 Top ten cited articles in the field of machine learning in solid organ transplantation

Title	First author	Journal	Publication year	Total citations
Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation	Torgyn Shaikhina	Biomedical Signal Processing and Control	2019	162
Machine learning algorithms outperform conventional regression models in predicting development of hepatocellular carcinoma	Amit Singal	American Journal of Gastroenterology	2013	152
Prediction of acute kidney injury after liver transplantation: Machine learning approaches vs. logistic regression model	Hyung-Chul Lee	Journal of Clinical Medicine	2018	96
Assessing rejection-related disease in kidney transplant biopsies based on archetypal analysis of molecular phenotypes	Jeff Reeve	JCI Insight	2017	90
Application of machine-learning models to predict tacrolimus stable dose in renal transplant recipients	Jie Tang	Scientific Reports	2017	83
Predicting the graft survival for heart-lung transplantation patients: An integrated data mining methodology	Asil Oztekin	International Journal of Medical Informatics	2009	79
Machine-learning algorithms predict graft failure after liver transplantation	Lawrence Lau	Transplantation	2017	76
Applying machine learning in liver disease and transplantation: A comprehensive review	Ashley Spann	Hepatology	2020	66
Predicting graft survival among kidney transplant recipients: A Bayesian decision support model	Kazim Topuz	Decision Support Systems	2018	64
Transcriptional trajectories of human kidney injury progression	Pietro Cippa	JCI Insight	2018	58