• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

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

作者信息

Kwong Allison J, Asrani Sumeet K

机构信息

Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA.

Hepatology, Baylor University Medical Center, Dallas, TX.

出版信息

Liver Transpl. 2018 Feb;24(2):161-163. doi: 10.1002/lt.24993.

DOI:10.1002/lt.24993
PMID:29211925
Abstract
摘要

相似文献

1
Artificial neural networks and liver transplantation: Are we ready for self-driving cars?人工神经网络与肝移植：我们准备好迎接自动驾驶汽车了吗？
Liver Transpl. 2018 Feb;24(2):161-163. doi: 10.1002/lt.24993.
2
Performance of multi-layer feedforward neural networks to predict liver transplantation outcome.多层前馈神经网络预测肝移植结果的性能
Methods Inf Med. 1996 Mar;35(1):12-8.
3
Validation of artificial neural networks as a methodology for donor-recipient matching for liver transplantation.验证人工神经网络作为肝移植供体-受者匹配方法的研究。
Liver Transpl. 2018 Feb;24(2):192-203. doi: 10.1002/lt.24870.
4
[Prediction of blood tacrolimus concentration in liver transplantation recipients by artificial neural network].[人工神经网络预测肝移植受者血液中他克莫司浓度]
Yao Xue Xue Bao. 2012 Sep;47(9):1134-40.
5
Prediction of significant fibrosis in hepatitis C virus infected liver transplant recipients by artificial neural network analysis of clinical factors.通过对临床因素进行人工神经网络分析预测丙型肝炎病毒感染的肝移植受者的显著纤维化
Eur J Gastroenterol Hepatol. 2006 Dec;18(12):1255-61. doi: 10.1097/01.meg.0000243885.55562.7e.
6
Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem.用于解决不平衡肝移植问题的动态加权进化序数神经网络
Artif Intell Med. 2017 Mar;77:1-11. doi: 10.1016/j.artmed.2017.02.004. Epub 2017 Feb 20.
7
Predicting patient survival after liver transplantation using evolutionary multi-objective artificial neural networks.利用进化多目标人工神经网络预测肝移植患者的生存情况。
Artif Intell Med. 2013 May;58(1):37-49. doi: 10.1016/j.artmed.2013.02.004. Epub 2013 Mar 13.
8
Appropriateness of a donor liver with respect to macrosteatosis: application of artificial neural networks to US images--initial experience.供体肝脏脂肪变性程度的适宜性：人工神经网络在超声图像中的应用——初步经验
Radiology. 2005 Mar;234(3):793-803. doi: 10.1148/radiol.2343040142. Epub 2005 Jan 21.
9
Ready or Not, Here We Go: Decision-Making Strategies From Artificial Intelligence Based on Deep Neural Networks.无论你是否准备好，我们都要开始了：基于深度神经网络的人工智能决策策略。
Neurosurgery. 2016 Jun;78(6):N11-2. doi: 10.1227/01.neu.0000484053.82181.f6.
10
Artificial neural networks: are they ready for use as clinical decision aids?人工神经网络：它们准备好用作临床决策辅助工具了吗？
Med Decis Making. 2000 Apr-Jun;20(2):243-4. doi: 10.1177/0272989X0002000210.

引用本文的文献

1
Development of a liver graft assessment expert machine-learning system: when the artificial intelligence helps liver transplant surgeons.肝移植评估专家机器学习系统的开发：人工智能如何助力肝移植外科医生
Front Surg. 2023 Sep 22;10:1048451. doi: 10.3389/fsurg.2023.1048451. eCollection 2023.
2
"Beyond MELD" - Emerging strategies and technologies for improving mortality prediction, organ allocation and outcomes in liver transplantation.“超越 MELD”-改善肝移植死亡率预测、器官分配和结局的新兴策略和技术。
J Hepatol. 2022 Jun;76(6):1318-1329. doi: 10.1016/j.jhep.2022.03.003.