Artificial neural networks and liver transplantation: Are we ready for self-driving cars?-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Artificial neural networks and liver transplantation: Are we ready for self-driving cars?

Published:2018-01-29 Issue:2 Volume:24 Page:161-163
ISSN:1527-6465
Container-title:Liver Transplantation
language:en
Short-container-title:Liver Transpl

Author:

Kwong Allison J.¹^ORCID,Asrani Sumeet K.²

Affiliation:

1. Division of Gastroenterology and Hepatology; Stanford University; Stanford CA

2. Hepatology; Baylor University Medical Center; Dallas TX

Funder

Baylor Foundation

National Institutes of Health

National Center for Advancing Translational Sciences

Clinical and Translational Science Award

Publisher

Wiley

Subject

Transplantation,Hepatology,Surgery

Reference20 articles.

1. Survival benefit-based deceased-donor liver allocation;Schaubel;Am J Transplant,2009

2. Survival benefit of liver transplantation: one size fits all or fits none?;Asrani;Hepatology,2009

3. The donor risk index: a decade of experience;Flores;Liver Transpl,2017

4. D-MELD, a simple predictor of post liver transplant mortality for optimization of donor/recipient matching;Halldorson;Am J Transplant,2009

5. Characteristics associated with liver graft failure: the concept of a donor risk index;Feng;Am J Transplant,2006

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Development of a liver graft assessment expert machine-learning system: when the artificial intelligence helps liver transplant surgeons;Frontiers in Surgery;2023-09-22

2. “Beyond MELD” – Emerging strategies and technologies for improving mortality prediction, organ allocation and outcomes in liver transplantation;Journal of Hepatology;2022-06

3. Artificial intelligence and organ transplantation: challenges and expectations;Current Opinion in Organ Transplantation;2020-06-01

4. Machine-learning algorithms for predicting results in liver transplantation: the problem of donor–recipient matching;Current Opinion in Organ Transplantation;2020-06-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3