THE PREDICTION OF REJECTION RISK IN KIDNEY TRANSPLANTATION: AN INTEGRATIVE REVIEW
DOI:
https://doi.org/10.48090/ciki.v1i1.1176Keywords:
Kidney transplantation; Post-transplantation; Rejection; Artificial intelligence; Integrative ReviewAbstract
Chronic Kidney Disease (CKD) is caused by a degeneration of kidney function in which transplantation is one of the treatment options adopted. The main Artificial Intelligence (AI) techniques applied to predict kidney graft rejection in the first-year post-transplantation are presented in this review. To this end, an integrative review on the subject was carried out, based on consultation of the databases: PubMed, Scielo, Embase and Lilacs, and found 122 articles, leaving 27 with greater relevance after applying the inclusion and exclusion criteria. Each research carried out is supported by AI practices that are more adequate to the variables provided by specialists and the amount of data made available to the researcher. Thus, the results of the inferences, although with precision that showed variations, usually satisfy the prediction of graft rejection with good accuracy.
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