• 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

Sensitivity and Specificity of a Machine Learning Algorithm to Identify Goals-of-care Documentation for Adults With Congenital Heart Disease at the End of Life.

作者信息

Steiner Jill M, Morse Christina, Lee Robert Y, Curtis J Randall, Engelberg Ruth A

机构信息

Division of Cardiology, University of Washington, Seattle, Washington, USA; Cambia Palliative Care Center of Excellence, University of Washington, Seattle, Washington, USA.

Internal Medicine Residency, School of Medicine, University of Washington, Seattle, Washington, USA.

出版信息

J Pain Symptom Manage. 2020 Sep;60(3):e33-e36. doi: 10.1016/j.jpainsymman.2020.06.018. Epub 2020 Jun 26.

DOI:10.1016/j.jpainsymman.2020.06.018
PMID:32599151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7484168/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eaf9/7484168/897b11e99af8/nihms-1618240-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eaf9/7484168/897b11e99af8/nihms-1618240-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eaf9/7484168/897b11e99af8/nihms-1618240-f0001.jpg

相似文献

1
Sensitivity and Specificity of a Machine Learning Algorithm to Identify Goals-of-care Documentation for Adults With Congenital Heart Disease at the End of Life.一种机器学习算法用于识别先天性心脏病成人临终时照护目标文件的敏感性和特异性
J Pain Symptom Manage. 2020 Sep;60(3):e33-e36. doi: 10.1016/j.jpainsymman.2020.06.018. Epub 2020 Jun 26.
2
Machine learning algorithms estimating prognosis and guiding therapy in adult congenital heart disease: data from a single tertiary centre including 10 019 patients.机器学习算法在成人先天性心脏病中的预后估计和治疗指导：来自单个三级中心的数据，包括 10019 例患者。
Eur Heart J. 2019 Apr 1;40(13):1069-1077. doi: 10.1093/eurheartj/ehy915.
3
Enhanced Critical Congenital Cardiac Disease Screening by Combining Interpretable Machine Learning Algorithms.通过结合可解释机器学习算法加强先天性心脏病重症筛查
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:1403-1406. doi: 10.1109/EMBC46164.2021.9630111.
4
Hospital resource utilization and presence of advance directives at the end of life for adults with congenital heart disease.先天性心脏病成人患者临终时的医院资源利用及预先医疗指示情况
Congenit Heart Dis. 2018 Sep;13(5):721-727. doi: 10.1111/chd.12638. Epub 2018 Sep 19.
5
Management of adults with cyanotic congenital heart disease.成人紫绀型先天性心脏病的管理。
Heart. 2015 Mar;101(6):485-94. doi: 10.1136/heartjnl-2012-301685. Epub 2014 Oct 9.
6
[Classification of heart sound signals in congenital heart disease based on convolutional neural network].基于卷积神经网络的先天性心脏病心音信号分类
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2019 Oct 25;36(5):728-736. doi: 10.7507/1001-5515.201806031.
7
Approaching End-of-Life Decisions in Adults with Congenital Heart Disease.成人先天性心脏病末期治疗决策。
Curr Cardiol Rep. 2020 Oct 10;22(12):173. doi: 10.1007/s11886-020-01428-5.
8
Congenital Heart Disease: The Remarkable Journey From the "Post-Mortem Room" to Adult Clinics.先天性心脏病：从“验尸房”到成人诊所的非凡历程。
Circ Res. 2017 Mar 17;120(6):895-897. doi: 10.1161/CIRCRESAHA.117.310830.
9
Are wide complex tachycardia algorithms applicable in children and patients with congenital heart disease?宽QRS波心动过速算法适用于儿童和先天性心脏病患者吗？
J Electrocardiol. 2010 Nov-Dec;43(6):694-700. doi: 10.1016/j.jelectrocard.2010.02.008. Epub 2010 Apr 10.
10
Transitional Care for Young Adults With Congenital Heart Disease: A Case Study.先天性心脏病青年成人的过渡性护理：一项案例研究。
J Pediatr Health Care. 2018 Mar-Apr;32(2):195-200. doi: 10.1016/j.pedhc.2017.10.005. Epub 2017 Dec 28.

引用本文的文献

1
Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.利用人工智能改善临床文档记录：一项系统综述。
Perspect Health Inf Manag. 2024 Jun 1;21(2):1d. eCollection 2024 Summer-Fall.
2
Presence and Content of Goals-of-Care Documentation for Patients With Adult Congenital Heart Disease at End-of-Life.成人先天性心脏病患者临终时医疗照护目标文件的存在情况与内容
JACC Adv. 2025 Apr;4(4):101645. doi: 10.1016/j.jacadv.2025.101645. Epub 2025 Mar 13.
3
Predictors of Documented Goals-of-Care Discussion for Hospitalized Patients With Chronic Illness.

本文引用的文献

1
Identifying Goals of Care Conversations in the Electronic Health Record Using Natural Language Processing and Machine Learning.使用自然语言处理和机器学习在电子健康记录中识别护理谈话目标
J Pain Symptom Manage. 2021 Jan;61(1):136-142.e2. doi: 10.1016/j.jpainsymman.2020.08.024. Epub 2020 Aug 25.
2
Deep Natural Language Processing Identifies Variation in Care Preference Documentation.深度自然语言处理识别护理偏好文档中的变化。
J Pain Symptom Manage. 2020 Jun;59(6):1186-1194.e3. doi: 10.1016/j.jpainsymman.2019.12.374. Epub 2020 Jan 9.
3
Natural Language Processing to Assess End-of-Life Quality Indicators in Cancer Patients Receiving Palliative Surgery.
住院慢性病患者记录的照护目标讨论的预测因素。
J Pain Symptom Manage. 2023 Mar;65(3):233-241. doi: 10.1016/j.jpainsymman.2022.11.012. Epub 2022 Nov 22.
4
Mixed-methods evaluation of three natural language processing modeling approaches for measuring documented goals-of-care discussions in the electronic health record.混合方法评估三种自然语言处理建模方法在电子健康记录中测量记录的目标关怀讨论的效果。
J Pain Symptom Manage. 2022 Jun;63(6):e713-e723. doi: 10.1016/j.jpainsymman.2022.02.006. Epub 2022 Feb 16.
自然语言处理评估接受姑息手术的癌症患者的临终质量指标。
J Palliat Med. 2019 Feb;22(2):183-187. doi: 10.1089/jpm.2018.0326. Epub 2018 Oct 17.
4
Extraction of Ejection Fraction from Echocardiography Notes for Constructing a Cohort of Patients having Heart Failure with reduced Ejection Fraction (HFrEF).从超声心动图记录中提取射血分数，以构建射血分数降低的心力衰竭（HFrEF）患者队列。
J Med Syst. 2018 Sep 25;42(11):209. doi: 10.1007/s10916-018-1066-7.
5
Hospital resource utilization and presence of advance directives at the end of life for adults with congenital heart disease.先天性心脏病成人患者临终时的医院资源利用及预先医疗指示情况
Congenit Heart Dis. 2018 Sep;13(5):721-727. doi: 10.1111/chd.12638. Epub 2018 Sep 19.
6
Measuring Processes of Care in Palliative Surgery: A Novel Approach Using Natural Language Processing.测量姑息手术中的照护过程：一种使用自然语言处理的新方法。
Ann Surg. 2018 May;267(5):823-825. doi: 10.1097/SLA.0000000000002579.
7
Knowledge of and preference for advance care planning by adults with congenital heart disease.先天性心脏病成年人对预先医疗指示的认知和偏好。
Am J Cardiol. 2012 Jun 15;109(12):1797-800. doi: 10.1016/j.amjcard.2012.02.027. Epub 2012 Mar 28.
8
End-of-life care in hospitalized adults with complex congenital heart disease: care delayed, care denied.住院成人复杂先天性心脏病的临终关怀：延迟的关怀，被拒绝的关怀。
Palliat Med. 2012 Jan;26(1):72-9. doi: 10.1177/0269216311407694. Epub 2011 Jun 22.
9
ACC/AHA 2008 guidelines for the management of adults with congenital heart disease: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Develop Guidelines on the Management of Adults With Congenital Heart Disease). Developed in Collaboration With the American Society of Echocardiography, Heart Rhythm Society, International Society for Adult Congenital Heart Disease, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons.美国心脏病学会/美国心脏协会2008年成人先天性心脏病管理指南：美国心脏病学会/美国心脏协会实践指南工作组（制定成人先天性心脏病管理指南写作委员会）报告。与美国超声心动图学会、心律学会、国际成人先天性心脏病学会、心血管造影和介入学会以及胸外科医师学会合作制定。
J Am Coll Cardiol. 2008 Dec 2;52(23):e143-e263. doi: 10.1016/j.jacc.2008.10.001.