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

Guidelines for Nursing Documentation I01:30

Guidelines for Nursing Documentation I

Quality documentation and reporting share essential characteristics that ensure they are practical and valuable resources for those who use them. These characteristics are:
Factual:  
The following points emphasize the significance of upholding accurate and unbiased documentation in healthcare.

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

Variability in epilepsy polygenic risk prediction across Taiwanese population and clinical cohorts.

Epilepsia·2026
Same author

Developing a clinical decision support tool for stratifying stroke risk in patients presenting with dizziness to the emergency department: A retrospective cohort study.

Digital health·2026
Same author

Enhanced Prediction of Atrial Fibrillation in Patients With Ischemic Stroke Through Electronic Medical Records and Text Mining: Algorithm Development and Validation.

JMIR medical informatics·2026
Same author

An Intelligent Trial Eligibility Screening Tool Using Natural Language Processing With a Block-Based Visual Programming Interface: Development and Usability Study.

JMIR medical informatics·2025
Same author

Taiwan's National Health Insurance Research Database (NHIRD): in the Era of Artificial Intelligence, Causal Inference, and Data Security.

Clinical epidemiology·2025
Same author

Multimodal Multitask Learning for Predicting Depression Severity and Suicide Risk Using Pretrained Audio and Text Embeddings: Methodology Development and Application.

JMIR medical informatics·2025
Same journal

Pregnancy-Related Clinical Codes in Unlikely Populations in Primary Care.

JMIR medical informatics·2026
Same journal

Selecting, Scaling, and Measuring the Value of Ambient AI in a Nonacademic Health System: Multiphase Pilot Study.

JMIR medical informatics·2026
Same journal

Prediction of Early Hospital Admission (≤24 Hours) After Stroke Using Machine Learning and Deep Learning: Multicenter Study From China.

JMIR medical informatics·2026
Same journal

Assessing the Feasibility and Acceptability of Implementing a Preclinic Vital Signs Assessment in Primary Care: Cross-Sectional Pilot Study.

JMIR medical informatics·2026
Same journal

Candidate Passive Sensor Suite Technologies for Tactical Combat Casualty Care Environments: Comparative Assessment Study.

JMIR medical informatics·2026
Same journal

Relevance of the uMap Collaborative Platform as Support for Choropleth Mapping: A Traffic‒Light Statistical Signal Atlas of All-Cause Mortality-First French Lockdown.

JMIR medical informatics·2026
查看所有相关文章

相关实验视频

Updated: May 28, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.6K

通过一对一的分类来消除临床缩写的模糊性:算法开发和验证研究

Sheng-Feng Sung1,2, Ya-Han Hu3, Chong-Yan Chen3

  • 1Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan.

JMIR medical informatics
|October 1, 2024
PubMed
概括
此摘要是机器生成的。

这项研究使用一对一 (OTA) 框架和从变压器 (BERT) 的双向编码器表示 (BERT) 来增强临床缩写扩展. 改进的方法有效地消除了医学缩写的模糊性,提高了信息提取和临床效率.

关键词:
缩写扩张扩张的缩写电子医疗记录 电子医疗记录自然语言处理自然语言处理.文本采矿 文本采矿是什么词语意义的明确化 词语意义的明确化

更多相关视频

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

15.9K

相关实验视频

Last Updated: May 28, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.6K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

15.9K

科学领域:

  • 自然语言处理自然语言处理.
  • 生物医学信息学 生物医学信息学
  • 计算语言学 计算语言学

背景情况:

  • 电子病历 (EMR) 包含有价值的患者数据,包括临床笔记.
  • 临床文本中的模两可和非标准化缩写阻碍了临床决策支持的自然语言处理 (NLP).
  • 有效的缩写分歧对于从医疗记录中提取准确信息至关重要.

研究的目的:

  • 加强一个对所有 (OTA) 框架,扩大临床缩写.
  • 通过开发上下文候选对和改进文字嵌入来优化双向编码器从变压器 (BERT) 模型的表示.
  • 通过使用真实世界医学数据,评估增强的OTA框架在扩大临床缩写中的有效性.

主要方法:

  • 使用了三个数据集:医学科目标题词语意义歧义,明尼苏达大学和Chia-Yi基督教医院.
  • 预处理和格式化的文本包含BERT的多体缩写.
  • 微调的预训练模型,ClinicalBERT和BlueBERT,生成训练和测试数据集对.

主要成果:

  • 蓝伯特实现了高精度 (例如,在MSH WSD数据集上95.41%的宏观精度).
  • 与基线模型 (LSTM,deepBioWSD,Word2Vec+SVM,BioWordVec+SVM) 相比,显著改善了宏观精度.
  • 在明尼苏达大学数据集上实现了98.40%的宏观精度.

结论:

  • 增强的一对所有 (OTA) 方法有效地消除了临床缩写的模糊性.
  • 这种方法显示出提高临床人员效率和研究效率的潜力.
  • 验证了优化BERT嵌入的实用性,以扩展临床缩写.