Development and validation of an artificial intelligence model for predicting post-transplant hepatocellular cancer recurrence

Dear Editor,In recent years,criteria based on the combinationof morphology and biology have been proposed forimproving the selection of hepatocellular cancer(HCC)patients waiting for liver transplantation(LT)[1,2].Since all the proposed models showed suboptimalresults in predicting the risk of postLT recurrence,aprediction model constructed using artificial intelligence(Al)could be an attractive way to surpass this limit[3,4].Therefore,the Time_Radiological-response_Alpha-fetoproteIN_Artificial-Intelligence(TRAIN-AI)modelwas developed,combining morphology and biology tumorvariables.