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

作者信息

Lai Quirino, De Stefano Carmine, Emond Jean, Bhangui Prashant, Ikegami Toru, Schaefer Benedikt, Hoppe-Lotichius Maria, Mrzljak Anna, Ito Takashi, Vivarelli Marco, Tisone Giuseppe, Agnes Salvatore, Ettorre Giuseppe Maria, Rossi Massimo, Tsochatzis Emmanuel, Lo Chung Mau, Chen Chao-Long, Cillo Umberto, Ravaioli Matteo, Lerut Jan Paul

机构信息

General Surgery and Organ Transplantation Unit, AOU Policlinico Umberto I, Sapienza University of Rome, Rome, Italy.

Data Science and Engineering, Polytechnic of Turin, Turin, Italy.

出版信息

Cancer Commun (Lond). 2023 Dec;43(12):1381-1385. doi: 10.1002/cac2.12468. Epub 2023 Oct 30.

DOI:10.1002/cac2.12468
PMID:37904670
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10693300/
Abstract
摘要

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本文引用的文献

1
The Toronto Postliver Transplantation Hepatocellular Carcinoma Recurrence Calculator: A Machine Learning Approach.多伦多肝移植后肝细胞癌复发计算器:一种机器学习方法。
Liver Transpl. 2022 Apr;28(4):593-602. doi: 10.1002/lt.26332. Epub 2021 Nov 5.
2
Novel Model to Predict HCC Recurrence after Liver Transplantation Obtained Using Deep Learning: A Multicenter Study.使用深度学习获得的预测肝移植后肝癌复发的新型模型:一项多中心研究
Cancers (Basel). 2020 Sep 29;12(10):2791. doi: 10.3390/cancers12102791.
3
Liver transplantation for hepatocellular carcinoma after successful treatment of macrovascular invasion - a multi-center retrospective cohort study.肝癌伴大血管侵犯经治疗后行肝移植的多中心回顾性队列研究。
Transpl Int. 2020 May;33(5):567-575. doi: 10.1111/tri.13586. Epub 2020 Feb 20.
4
Charting the Path Forward for Risk Prediction in Liver Transplant for Hepatocellular Carcinoma: International Validation of HALTHCC Among 4,089 Patients.为肝癌肝移植的风险预测绘制前进道路:4089 例患者中 HALTHCC 的国际验证。
Hepatology. 2020 Feb;71(2):569-582. doi: 10.1002/hep.30838. Epub 2019 Aug 19.
5
Metroticket 2.0 Model for Analysis of Competing Risks of Death After Liver Transplantation for Hepatocellular Carcinoma.Metroticket 2.0 模型分析肝癌肝移植术后死亡的竞争风险。
Gastroenterology. 2018 Jan;154(1):128-139. doi: 10.1053/j.gastro.2017.09.025. Epub 2017 Oct 5.
6
Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.预测未来——大数据、机器学习与临床医学。
N Engl J Med. 2016 Sep 29;375(13):1216-9. doi: 10.1056/NEJMp1606181.
7
A Novel Prognostic Index in Patients With Hepatocellular Cancer Waiting for Liver Transplantation: Time-Radiological-response-Alpha-fetoprotein-INflammation (TRAIN) Score.一种新型的肝癌患者肝移植等待期预后指标:时间-影像学-甲胎蛋白-炎症(TRAIN)评分。
Ann Surg. 2016 Nov;264(5):787-796. doi: 10.1097/SLA.0000000000001881.
8
Liver transplantation for hepatocellular carcinoma: a model including α-fetoprotein improves the performance of Milan criteria.肝癌肝移植:包含甲胎蛋白的模型可改善米兰标准的性能。
Gastroenterology. 2012 Oct;143(4):986-94.e3; quiz e14-5. doi: 10.1053/j.gastro.2012.05.052. Epub 2012 Jun 29.
9
A time-dependent discrimination index for survival data.生存数据的时间依赖性判别指数。
Stat Med. 2005 Dec 30;24(24):3927-44. doi: 10.1002/sim.2427.
10
Liver transplantation for the treatment of small hepatocellular carcinomas in patients with cirrhosis.肝移植治疗肝硬化患者的小肝细胞癌
N Engl J Med. 1996 Mar 14;334(11):693-9. doi: 10.1056/NEJM199603143341104.