Current opinion in organ transplantation
Aug 1, 2020
PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical, immunological and genetic variables. Artificial intelligence tools, such as artificial neural networks (ANNs) or classification and regression trees ...
Studies in health technology and informatics
Aug 21, 2019
Kidney transplantation is recommended for patients with End-Stage Renal Disease (ESRD). However, complications, such as graft rejection are hard to predict due to donor and recipient variability. This study discusses the role of machine learning (ML)...
Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society
Feb 1, 2018
In 2014, we reported a model for donor-recipient (D-R) matching in liver transplantation (LT) based on artificial neural networks (ANNs) from a Spanish multicenter study (Model for Allocation of Donor and Recipient in España [MADR-E]). The aim is to ...
BACKGROUND: The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritiz...
BACKGROUND: Minimally invasive approaches to kidney transplantation (KT) have been described recently. However, information concerning perioperative management in these patients is lacking. Accordingly, in the current study, we describe our periopera...
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