Jove
Visualize
联系我们

相关概念视频

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.6K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.6K

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

Resilience as a Mediator Between Burnout and Health Among Nurses During the COVID-19 Pandemic: A Cross-Sectional Survey in Late 2021.

Nursing open·2026
Same author

Political Influence, Facilitators and Barriers in the Decision-Making Processes of Executive Nurse Leaders During the COVID-19 Pandemic in Spain: An Ethnographic Study.

Journal of nursing management·2025
Same author

Prediction of Metastasis in Paragangliomas and Pheochromocytomas Using Machine Learning Models: Explainability Challenges.

Sensors (Basel, Switzerland)·2025
Same author

A Video Mosaicing-Based Sensing Method for Chicken Behavior Recognition on Edge Computing Devices.

Sensors (Basel, Switzerland)·2024
Same author

Using Large Language Models to Enhance the Reusability of Sensor Data.

Sensors (Basel, Switzerland)·2024
Same author

A Comprehensive Study on Pain Assessment from Multimodal Sensor Data.

Sensors (Basel, Switzerland)·2023
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

相关实验视频

Updated: Jun 26, 2025

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

使用深度学习技术的传感技术自动生成临床报告.

Celia Cabello-Collado1, Javier Rodriguez-Juan1, David Ortiz-Perez1

  • 1Department of Computer Technology, University of Alicante, 03080 Alicante, Spain.

Sensors (Basel, Switzerland)
|May 11, 2024
PubMed
概括

这项研究使用先进的传感器和人工智能自动转录和总结患者与医生的对话,减少医疗保健专业人员的行政任务. 这种创新方法提高了临床文档的效率和准确性.

关键词:
音频传感器 音频传感器医疗保健 医疗保健 医疗保健 医疗保健多式联运数据是多式联运数据.文本总结 文本总结 文本总结变压器 变压器 变压器

更多相关视频

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

737
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K

相关实验视频

Last Updated: Jun 26, 2025

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
DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

737
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K

科学领域:

  • 生物医学信息学 生物医学信息学
  • 医疗保健中的人工智能
  • 临床文档 临床文档

背景情况:

  • 临床文档是医疗保健专业人员的一项耗时的行政任务.
  • 准确和有效的文档对于患者护理和医疗记录保存至关重要.
  • 临床文档的现有方法可能是手动的,容易出现错误.

研究的目的:

  • 开发和评估一种基于传感器的新型系统,用于自动化临床文档.
  • 提高从患者与医生的互动中生成临床笔记的准确性和效率.
  • 通过自动总结来减少医疗保健提供者的行政负担.

主要方法:

  • 利用先进的传感技术来捕捉患者与医生的互动线索 (例如,语音模式,语调).
  • 集成自动语音识别 (ASR) 用于实时转录口语对话.
  • 采用深度学习模型,特别是变压器模型,用于信息提取和对话总结.

主要成果:

  • 该系统展示了实时感知和理解患者与医生的互动.
  • 在总结复杂的医疗讨论中获得0.57的最大ROUGE-1得分.
  • 成功自动转录和总结,生成简洁的临床文档.

结论:

  • 基于传感器的方法在自动化临床文档方面表现有前途.
  • 这项技术可以显著减轻医疗保健专业人员的行政工作量.
  • 该方法提高了临床文档的效率和可靠性,可能改善医疗保健结果.