Natural Language Processing for Adjudication of Heart Failure in the Electronic Health Record.
作者信息
Cunningham Jonathan W, Singh Pulkit, Reeder Christopher, Lau Emily S, Khurshid Shaan, Wang Xin, Ellinor Patrick T, Lubitz Steven A, Batra Puneet, Ho Jennifer E
出版信息
JACC Heart Fail. 2023 Jul;11(7):852-854. doi: 10.1016/j.jchf.2023.02.012. Epub 2023 Mar 5.
Abstract
摘要
相似文献
1
Natural Language Processing for Adjudication of Heart Failure in the Electronic Health Record.电子健康记录中用于判定心力衰竭的自然语言处理
JACC Heart Fail. 2023 Jul;11(7):852-854. doi: 10.1016/j.jchf.2023.02.012. Epub 2023 Mar 5.
2
Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials.用于判定全球临床试验中心力衰竭住院情况的自然语言处理
Circ Heart Fail. 2025 Jan;18(1):e012514. doi: 10.1161/CIRCHEARTFAILURE.124.012514. Epub 2024 Nov 16.
3
Clinical and research applications of natural language processing for heart failure.自然语言处理在心力衰竭中的临床与研究应用
Heart Fail Rev. 2025 Mar;30(2):407-415. doi: 10.1007/s10741-024-10472-0. Epub 2024 Dec 19.
4
Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study.从两家医院的电子健康记录中识别充血性心力衰竭患者：回顾性研究
JMIR Med Inform. 2025 Apr 10;13:e64113. doi: 10.2196/64113.
5
Automated identification of postoperative complications within an electronic medical record using natural language processing.利用自然语言处理技术在电子病历中自动识别术后并发症。
JAMA. 2011 Aug 24;306(8):848-55. doi: 10.1001/jama.2011.1204.
6
Automatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records.利用电子健康记录中的临床记录进行文本分析，自动识别心力衰竭诊断标准。
Int J Med Inform. 2014 Dec;83(12):983-92. doi: 10.1016/j.ijmedinf.2012.12.005. Epub 2013 Jan 11.
7
Text mining occupations from the mental health electronic health record: a natural language processing approach using records from the Clinical Record Interactive Search (CRIS) platform in south London, UK.从精神健康电子健康记录中挖掘文本职业信息：使用英国伦敦南部临床记录交互检索（CRIS）平台记录的自然语言处理方法。
BMJ Open. 2021 Mar 25;11(3):e042274. doi: 10.1136/bmjopen-2020-042274.
8
Development and Evaluation of a Natural Language Processing Annotation Tool to Facilitate Phenotyping of Cognitive Status in Electronic Health Records: Diagnostic Study.开发和评估一种自然语言处理标注工具以促进电子健康记录中认知状态的表型分析：诊断研究。
J Med Internet Res. 2022 Aug 30;24(8):e40384. doi: 10.2196/40384.
9
Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes.通过对护理记录的自然语言处理，描绘常见慢性病中共同和独特的症状群。
Res Nurs Health. 2021 Dec;44(6):906-919. doi: 10.1002/nur.22190. Epub 2021 Oct 12.
10
Discovering and identifying New York heart association classification from electronic health records.从电子健康记录中发现和识别纽约心脏协会分类。
BMC Med Inform Decis Mak. 2018 Jul 23;18(Suppl 2):48. doi: 10.1186/s12911-018-0625-7.
引用本文的文献
1
Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone.与仅使用诊断代码相比，自然语言处理可提高对新冠肺炎的可靠识别率。
Am J Epidemiol. 2025 Jul 30. doi: 10.1093/aje/kwaf162.
2
Frailty: Can a Biological Aging Marker Enhance Precision Risk Assessment of Cancer Therapy Cardiotoxicity?衰弱：一种生物衰老标志物能否增强癌症治疗心脏毒性的精准风险评估？
JACC CardioOncol. 2025 Feb;7(2):122-124. doi: 10.1016/j.jaccao.2025.01.004.
3
Clinical and research applications of natural language processing for heart failure.自然语言处理在心力衰竭中的临床与研究应用
Heart Fail Rev. 2025 Mar;30(2):407-415. doi: 10.1007/s10741-024-10472-0. Epub 2024 Dec 19.
4
Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials.用于判定全球临床试验中心力衰竭住院情况的自然语言处理
Circ Heart Fail. 2025 Jan;18(1):e012514. doi: 10.1161/CIRCHEARTFAILURE.124.012514. Epub 2024 Nov 16.
5
Artificial Intelligence in Cardiovascular Clinical Trials.人工智能在心血管临床试验中的应用。
J Am Coll Cardiol. 2024 Nov 12;84(20):2051-2062. doi: 10.1016/j.jacc.2024.08.069.
6
Frequency of Electrocardiogram-Defined Cardiac Conduction Disorders in a Multi-Institutional Primary Care Cohort.多机构初级保健队列中心电图定义的心脏传导障碍的发生率
JACC Adv. 2024 May 24;3(7):101004. doi: 10.1016/j.jacadv.2024.101004. eCollection 2024 Jul.
7
Artificial intelligence approaches for phenotyping heart failure in U.S. Veterans Health Administration electronic health record.美国退伍军人事务部电子健康记录中基于人工智能的心力衰竭表型分析方法。
ESC Heart Fail. 2024 Oct;11(5):3155-3166. doi: 10.1002/ehf2.14787. Epub 2024 Jun 14.
本文引用的文献
1
Cohort design and natural language processing to reduce bias in electronic health records research.队列设计与自然语言处理以减少电子健康记录研究中的偏倚
NPJ Digit Med. 2022 Apr 8;5(1):47. doi: 10.1038/s41746-022-00590-0.
2
Age dependent associations of risk factors with heart failure: pooled population based cohort study.年龄相关因素与心力衰竭的关系：基于人群的 pooled 队列研究。
BMJ. 2021 Mar 23;372:n461. doi: 10.1136/bmj.n461.
Zotero 插件