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

Assessment of Ventilation I: Respiratory Rate01:20

Assessment of Ventilation I: Respiratory Rate

1.3K
Assessment of Ventilation
A Ventilation assessment is critical for monitoring a patient's health status. Respiration, one of the most accessible vital signs, provides insights into the function of numerous body systems and can indicate serious health issues, such as brainstem injuries from head trauma.
Critical Guidelines for Assessing Ventilation:
1.3K
Mechanical Ventilation II: Invasive Ventilation01:23

Mechanical Ventilation II: Invasive Ventilation

253
Ventilators are essential medical equipment used to aid patients with respiratory difficulties. Their primary function is to assist or replace spontaneous breathing by providing mechanical ventilation. There are two general classes of mechanical ventilators: negative-pressure and positive-pressure ventilators.
Negative-Pressure Ventilators
Negative-pressure ventilators create a vacuum around the chest or body to draw air into the lungs, simulating breathing. This method does not require an...
253
Assessment of Ventilation II: Respiratory Depth and Rhythm01:29

Assessment of Ventilation II: Respiratory Depth and Rhythm

1.8K
Respiratory Depth
Respiratory depth measures the volume of air inhaled or exhaled during a breath. It can vary from shallow to deep and typically remains consistent when a person is at rest or asleep. Occasionally, individuals will automatically inhale deeply, known as sighing, which inflates the lungs with more air than normal breathing.
To assess respiratory depth, observe the degree of chest excursion or movement:
1.8K
Mechanical Ventilation I: Indication and Settings01:29

Mechanical Ventilation I: Indication and Settings

932
Mechanical ventilation is a life-saving technique for managing acute respiratory failure and other respiratory complications. The process involves using a machine known as a ventilator to supply oxygen to the lungs and assist in removing carbon dioxide. It serves as a bridge to long-term mechanical ventilation or a temporary measure until ventilatory support is discontinued. The ventilator can maintain this function for a prolonged period, providing critical support for patients until they can...
932
Mechanical Ventilation III: Noninvasive Ventilation01:23

Mechanical Ventilation III: Noninvasive Ventilation

224
Noninvasive positive-pressure ventilation (NIPPV), continuous positive airway pressure (CPAP), and bilevel positive airway pressure (BiPAP) are essential methods in respiratory care. These ventilation techniques offer unique benefits for patients with various respiratory conditions, providing adequate support without requiring intubation. Let's explore how each method is crucial in improving patient outcomes and enhancing respiratory therapy.
Noninvasive Positive-Pressure Ventilation...
224
Ventilatory Modes01:14

Ventilatory Modes

431
Mechanical ventilators are life-saving devices that support or replace spontaneous breathing. They deliver breaths to patients through varying methods known as ventilator modes. Understanding these modes is critical for healthcare providers managing patients with respiratory failure.
There are three ventilatory modes: full support, partial support, and spontaneous. These are described below.
Full Support Modes
Full support modes include controlled mechanical ventilation, continuous mandatory...
431

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

Airway wall thickness and PRISm are associated with cognitive impairment in individuals with cigarette smoking exposure.

Respiratory research·2026
Same author

Reply to Liu et al.: Beyond Frequency: Rethinking Exacerbation Risk in COPD.

American journal of respiratory and critical care medicine·2026
Same author

Beyond spirometry in COPD: expanding the diagnostic paradigm.

ERJ open research·2026
Same author

Performance of multivariable risk prediction algorithms in predicting COPD exacerbations: a population-based study.

Thorax·2026
Same author

Summary of Research: Dupilumab for Chronic Obstructive Pulmonary Disease with Type 2 Inflammation: A Pooled Analysis of Two Phase 3, Randomised, Double-Blind, Placebo-Controlled Trials.

Pulmonary therapy·2026
Same author

The Utility of Advanced Imaging in COPD: Diagnosis, Prognosis, and Treatment-introductory Editorial.

The British journal of radiology·2026

相关实验视频

Updated: Sep 10, 2025

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns
08:34

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns

Published on: September 16, 2019

11.7K

基于机器学习的真实通风限制检测

Pratim Saha1, Muhammad F A Chaudhary2, Akm Shahariar Azad Rabby1

  • 1Center for Lung Analytics and Imaging Research, University of Alabama at Birmingham, Birmingham, AL, 35294, USA; Department of Computer Science, University of Alabama at Birmingham, AL, 35294, USA.

Respiratory medicine
|August 21, 2025
PubMed
概括

一个新的机器学习模型使用螺旋计和患者人口统计学准确检测真实呼吸限制,减少了额外的肺体积测试的需要. 这种人工智能工具可以提高肺部限制的诊断准确性.

关键词:
肺部的体积机器学习螺旋测量限制风机限制

更多相关视频

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit
05:56

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit

Published on: September 6, 2024

3.4K
Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
09:42

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography

Published on: January 24, 2025

706

相关实验视频

Last Updated: Sep 10, 2025

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns
08:34

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns

Published on: September 16, 2019

11.7K
Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit
05:56

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit

Published on: September 6, 2024

3.4K
Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
09:42

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography

Published on: January 24, 2025

706

科学领域:

  • 肺部医学
  • 在医疗保健中的机器学习
  • 诊断工具

背景情况:

  • 在检测真实呼吸器限制方面,单独使用螺旋计的准确性有限 (50%).
  • 这需要进行额外的肺体积测试以进行准确的诊断.
  • 需要改进的方法来识别真正的呼吸限制.

研究的目的:

  • 开发一种新的肺部限制检测工具.
  • 该工具将精神测量数据与患者的人口信息相结合.
  • 目的是提高诊断准确度,减少对肺体积测试的依赖.

主要方法:

  • 分析了21062名参与者的精神测量和肺体积数据.
  • 开发一个使用螺旋计 (FEV1,FVC,FEV1/FVC,FEV1%pred,FVC%pred) 和人口特征 (年龄,性别,BMI) 的LightGBM机器学习模型.
  • 通过ROC分析评估表现的不同队列的模型培训和评估.

主要成果:

  • 开发的LightGBM模型的准确度为0. 78 (95% CI为0. 77-0. 80) 和AUC为0. 89 (95% CI为0. 88- 0. 90).
  • 与单独的精神测量相比,该模型的性能优越,灵敏度为0. 74 (95% CI为0. 72- 0. 75) 和特异性为0. 86 (95% CI为0. 84- 0. 87).
  • 仅限于限制性精神测量模式的确切度为0.61以检测真正的呼吸器限制.

结论:

  • 机器学习模型结合精神测量和人口统计数据可以有效检测真正的呼吸限制.
  • 这种人工智能驱动的方法显著提高了诊断准确度,
  • 该模型显示可能减少额外,更复杂的肺体积测试的要求.