| 7 | Development and validation of an artificial intelligence model for predicting post-transplant hepatocellular cancer recurrence显示文摘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. | Quirino Lai Carmine De Stefano Jean Emond Prashant Bhangui Toru Ikegami Benedikt Schaefer Maria Hoppe-Lotichius Anna Mrzljak Takashi Ito Marco Vivarelli Giuseppe Tisone Salvatore Agnes Giuseppe Maria Ettorre Massimo Rossi Emmanuel Tsochatzis Chung Mau Lo Chao-Long Chen Umberto Cillo Matteo Ravaioli Jan Paul Lerut the EurHeCaLT and the West-East LT Study Group | 2023 | Cancer Communications2023，43，12： | 0 |
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