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Updated: May 12, 2026

Mouse Kidney Transplantation: Models of Allograft Rejection
Published on: October 11, 2014
[Artificial intelligence in kidney transplant pathology]
Roman David Bülow1, Yu-Chia Lan1, Kerstin Amann2
1Institut für Pathologie, Sektion Nephropathologie, Universitätsklinikum RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Deutschland.
Background:
Artificial intelligence (AI) systems have showed promising results in digital pathology, including digital nephropathology and specifically also kidney transplant pathology.
Aim:
Summarize the current state of research and limitations in the field of AI in kidney transplant pathology diagnostics and provide a future outlook.
Materials And Methods:
Literature search in PubMed and Web of Science using the search terms "deep learning", "transplant", and "kidney". Based on these results and studies cited in the identified literature, a selection was made of studies that have a histopathological focus and use AI to improve kidney transplant diagnostics.
Results And Conclusion:
Many studies have already made important contributions, particularly to the automation of the quantification of some histopathological lesions in nephropathology. This likely can be extended to automatically quantify all relevant lesions for a kidney transplant, such as Banff lesions. Important limitations and challenges exist in the collection of representative data sets and the updates of Banff classification, making large-scale studies challenging. The already positive study results make future AI support in kidney transplant pathology appear likely.
Related Concept Videos
Kidney Transplant I: Introduction
Kidney Transplant II: Surgical Procedure
Kidney Transplant III: Nursing Management
Imaging Studies I: Kidney, Ureter, and Bladder Studies
Acute Kidney Injury IV: Diagnostic Studies and Prevention

