Related Experiment Video
Updated: Jul 13, 2025

Robot-Assisted Kidney Transplantation
Published on: July 19, 2021
[Prediction of renal transplantation outcome using artificial neural networks and investigating important risk
Abolfazl Zanghaei Abolfazl Zanghaei1,2,3,4, Zohreh Rostami Zohreh Rostami1,2,3,4, Ali Ameri Ali Ameri1,2,3,4
1Department of Biomedical Engineering and Biophysics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background:
Renal Transplantation is the final choice for some patients with ESRD (End-Stage Renal Disease), but some transplantations suffer from acute or chronic rejection, so its very important to predict the outcome of transplantation.
Method:
s. The dataset was extracted from records of 4572 patients with kidney transplantations. We applied an Artificial Neural Network (ANN) model to predict transplantation outcome. Moreover, novel features have been explored which enhanced the prediction performance.
Results:
The results show that the well configured neural networks can predict renal transplant outcome with a sensitivity and specificity of higher than 86%. The results show creatinine is the most important risk factor that affects the renal transplantation outcome.
Conclusion:
The designed neural networks can properly predict the transplantation outcome with the accuracy of 86%. Recipient creatinine is the most important variable in the prediction of the renal outcome.
Related Concept Videos
Kidney Transplant I: Introduction
Kidney Transplant III: Nursing Management
Kidney Transplant II: Surgical Procedure

