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Review
. 2021 Jul 18;11(7):277-289.
doi: 10.5500/wjt.v11.i7.277.

Artificial intelligence and kidney transplantation

Nurhan Seyahi  1 , Seyda Gul Ozcan  2
Affiliations
Review

Artificial intelligence and kidney transplantation

Nurhan Seyahi et al. World J Transplant. .

Abstract

Artificial intelligence and its primary subfield, machine learning, have started to gain widespread use in medicine, including the field of kidney transplantation. We made a review of the literature that used artificial intelligence techniques in kidney transplantation. We located six main areas of kidney transplantation that artificial intelligence studies are focused on: Radiological evaluation of the allograft, pathological evaluation including molecular evaluation of the tissue, prediction of graft survival, optimizing the dose of immunosuppression, diagnosis of rejection, and prediction of early graft function. Machine learning techniques provide increased automation leading to faster evaluation and standardization, and show better performance compared to traditional statistical analysis. Artificial intelligence leads to improved computer-aided diagnostics and quantifiable personalized predictions that will improve personalized patient care.

Keywords: Artificial intelligence; Deep learning; Kidney transplantation; Machine learning, Neuronal networks; Support vector machines.

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Conflict of interest statement

Conflict-of-interest statement: The authors declare no conflict of interest for this article.

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