Abstract

Renal transplantation is now widely regarded as the best treatment option for patients with end-stage renal failure in terms of survival and quality of life. It is of extremely importance to identify the potential risk factors for successful renal transplantation. The number of studies related to artificial intelligence (AI) applications in renal transplant patients grows by the day. In these studies, AI is used a wide range from pathological evaluation to immunosuppressive drug doses. Machine learning-based models that are AI algorithms perform to be superior to the traditional statistical method for predicting graft survival and rapidly provides analyzing of data. In recent years, the number of studies is increased using AI for renal transplants. In this review we aimed to examine the AI algorithms for predicting graft survival in renal transplantation.