Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

913
Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
913
Purpose of Health Records II01:19

Purpose of Health Records II

1.0K
Health records serve various essential purposes in the healthcare system. Here are some key purposes:
1.0K
Integrated Healthcare System01:20

Integrated Healthcare System

1.8K
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
1.8K
Purpose of Health Records I01:11

Purpose of Health Records I

1.3K
The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
1.3K
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

915
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
915
Nursing Clinical Information System01:27

Nursing Clinical Information System

864
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
864

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Early prediction of postoperative delirium in major surgery patients using multimodal preoperative EHR and medical notes: a retrospective cohort study in the Indiana network for patient care.

BMJ public health·2026
Same author

Predicting Childhood Obesity Using Machine Learning: Practical Considerations.

BioMedInformatics·2026
Same author

Prevalence of Multiple Chronic Conditions in Older Adults with Undiagnosed Mild Cognitive Impairment and Alzheimer's Disease and Related Dementias in Primary Care.

Clinical interventions in aging·2025
Same author

Harnessing the Power of Technology to Transform Delirium Severity Measurement in the Intensive Care Unit: Protocol for a Prospective Cohort Study.

JMIR research protocols·2025
Same author

Mobile Telehealth Intervention to Support Care Partners of Patients With Alzheimer Disease and Related Dementias (I-CARE 2): Protocol for a Randomized Effectiveness Clinical Trial.

JMIR research protocols·2025
Same author

Association of cardiovascular disease with dementia: A longitudinal analysis using National Alzheimer's Coordinating Center data.

Journal of Alzheimer's disease reports·2025

相关实验视频

Updated: Sep 10, 2025

Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients
03:47

Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients

Published on: July 12, 2024

872

常规护理电子健康记录 (EHR) 的多模式融合:一个范围审查

Zina Ben-Miled1, Jacob A Shebesh2, Jing Su3

  • 1Phillip M. Drayer Department of Electrical and Computer Engineering, Lamar University, Cherry Building, Beaumont, TX 77705, USA.

Information (Basel)
|August 22, 2025
PubMed
概括

这次范围审查突出了电子健康记录 (EHR) 数据元素定义和融合架构分类中的不一致性. 在临床决策支持中制定标准化指导方针对于有效的多模式电子病历数据融合至关重要.

关键词:
电子健康记录机器学习模式多模式融合变压器

更多相关视频

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.3K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

相关实验视频

Last Updated: Sep 10, 2025

Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients
03:47

Author Spotlight: Workflow for Integrating POCUS Data into EHR for Managing Heart Failure Patients

Published on: July 12, 2024

872
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.3K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

科学领域:

  • 医疗保健中的人工智能
  • 卫生信息学
  • 临床决策支持系统

背景情况:

  • 电子健康记录 (EHR) 在医疗保健中广泛使用,收集各种患者数据,包括人口统计,诊断,药物,笔记,生命体征和实验室结果.
  • 这些多模式电子健康记录数据具有丰富的语义,概念和时间信息,为先进的临床决策提供了潜在支持.
  • 最近的生成学习技术在融合这些异构的电子健康记录数据元素以提高医疗保健决策方面表现有前途.

研究的目的:

  • 对融合多式联络日常护理电子病历数据的技术进行范围审查.
  • 综合融合架构,输入数据元素和应用领域的差异.
  • 发现研究缺陷,促进融合技术的再利用,以获得新的临床结果.

主要方法:

  • 在Google Scholar上进行了全面的文献搜索,以使用2018-2023年多式联络日常护理EHR数据,寻找具有高影响力的融合架构.
  • 该审查遵循了PRISMA扩展范围审查的指导方针.
  • 研究结果以主题和比较方式进行分析.

主要成果:

  • 作为输入方式使用的EHR数据元素缺乏标准化定义,经常忽视数据源,编码和概念级别.
  • 建议对融合架构进行修订分类,将融合与学习区分开来,并在编码,表示和决策层中对并发学习进行计算.
  • 目前预训练的编码模型在处理时间和语义信息方面存在不一致,限制了它们的重用.

结论:

  • 目前的EHR融合架构主要依赖于逐个设计的方法.
  • 需要制定指导方针,为各种医疗应用设计高效的多模式.
  • 准则应强调模式组合,转移学习,共同学习和语义/时间编码的最佳实践,以促进重复使用.