公开(公告)号：US20240404707A1

公开(公告)日：2024-12-05

申请号：US18688105

申请日：2022-09-02

Applicant: UNIVERSITY OF PITTSBURGH-OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION

Inventor： Jianhua LUO ,  Aatur Dilip SINGHI ,  Baoguo REN ,  Chien-Cheng TSENG ,  George MICHALOPOULOS ,  Michael A. NALESNIK ,  Michelle A. WOOD-TRAGESER ,  Shuchang LIU ,  Yanping YU

IPC: G16H50/30 ,  G16B25/10 ,  G16B40/20 ,  G16H50/20

Abstract: Described herein are prediction models based on the transcriptomic, exomic, and/or radiological analyses on tissue samples to predict the likelihood of the original cancer (such as Hepatocellular carcinoma (HCC)) recurrence into the liver transplant. An example computer implemented method for predicting the likelihood of liver cancer recurrence 5 into a liver transplant includes receiving gene expression data related to a liver tissue sample for a subject having a liver cancer, inputting the gene expression data into a trained machine learning model, and predicting, using the trained machine learning model, a risk of recurrence of the liver cancer in the subject after liver transplantation.