Applications of neural networks in liver transplantation

The use of neural networks(NNs)as a cutting-edge technique in the medical field has drawn considerable attention.NN models“learn”from a large amount of data and then find corresponding clinical patterns that are challenging for clinicians to recognize.In this study,we focus on liver transplantation(LT),which is an effective treatment for end-stage liver diseases.The management before and after LT produces a massive quantity of medical data,which can be fully processed by NNs.We describe recent progress in the clinical application of NNs to LT in five respects:pre-transplantation evaluation of the donor and recipient,recipient outcome prediction,allocation system development,operation monitoring,and post-transplantation complication prediction.This review provides clinicians and researchers with a description of forefront applications of NNs in the field of LT and discusses prospects and pitfalls.