Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies01:27

Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies

2.5K
Assessing and diagnosing Chronic Obstructive Pulmonary Disease (COPD) involves a detailed approach that includes a comprehensive review of medical history, physical examination, and a variety of diagnostic tests. This thorough evaluation is essential to ensure an accurate diagnosis and guide effective management strategies.
Medical History
2.5K
Chronic Obstructive Pulmonary Disease-I: Introduction01:20

Chronic Obstructive Pulmonary Disease-I: Introduction

2.8K
Chronic Obstructive Pulmonary Disease (COPD) is a long-lasting respiratory condition requiring continuous attention and care. It is a progressive lung disease that leads to breathing challenges due to airflow obstruction. It manifests as persistent respiratory symptoms and restricted airflow resulting from abnormalities in the airways and alveoli, usually due to long-term exposure to harmful particles or gases. COPD mainly consists of two primary conditions: emphysema and chronic bronchitis.
2.8K
Chronic Obstructive Pulmonary Disease01:22

Chronic Obstructive Pulmonary Disease

1.1K
COPD is defined as a heterogeneous lung condition marked by persistent respiratory symptoms such as dyspnea, cough, and sputum production, caused by abnormalities in the airways that cause airflow obstruction.
Smoking is a primary risk factor for COPD, with over 80% of patients having a history of it. Patients typically experience progressive dyspnea or labored breathing, frequent coughing, and recurrent pulmonary infections. Many eventually succumb to respiratory failure, characterized by...
1.1K
COPD: Management Using Bronchodilators and Corticosteroids01:26

COPD: Management Using Bronchodilators and Corticosteroids

174
Chronic obstructive pulmonary isease (COPD) involves a group of progressive lung disorders characterized by persistent airflow limitation and chronic respiratory symptoms. Asthma-COPD Overlap Syndrome (ACOS), encompassing features of both asthma and Chronic obstructive pulmonary disease (COPD), is a group of progressive lung disorders that includes chronic bronchitis, emphysema, and refractory (non-reversible) asthma. ACOS leads to complex clinical presentations that combine the inflammatory...
174
COPD: Pathogenesis and Clinical Features01:20

COPD: Pathogenesis and Clinical Features

228
Chronic obstructive pulmonary disease (COPD) is a group of lung conditions that progressively worsen over time, including chronic bronchitis and emphysema. This cluster of diseases collectively leads to a gradual and irreversible decline in lung function over time.
The primary cause for the onset of COPD is cigarette smoking and exposure to air pollution. These hazardous factors initiate a chain reaction within the lungs, resulting in chronic inflammation, damage to the airways, and a...
228
Chronic Obstructive Pulmonary Disease-V: Management01:29

Chronic Obstructive Pulmonary Disease-V: Management

2.5K
Managing Chronic Obstructive Pulmonary Disease (COPD) involves a multifaceted approach to reduce symptoms, prevent exacerbations, improve overall health status, and slow disease progression. Key strategies include lifestyle modifications, pharmacotherapy, supportive therapies, and, in some cases, surgery. Here is an overview of the primary COPD management strategies:
Smoking Cessation
2.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Synergistic Effects of Tetrandrine with Posaconazole Against Aspergillus fumigatus.

Microbial drug resistance (Larchmont, N.Y.)·2017
Same author

A novel NHS mutation causes Nance-Horan Syndrome in a Chinese family.

BMC medical genetics·2017
Same author

Positively charged polypeptide nanogel enhances mucoadhesion and penetrability of 10-hydroxycamptothecin in orthotopic bladder carcinoma.

Journal of controlled release : official journal of the Controlled Release Society·2017
Same author

Methods used to study the oligomeric structure of G-protein-coupled receptors.

Bioscience reports·2017
Same author

Patterns of Early Rejection in Renal Retransplantation: A Single-Center Experience.

Journal of immunology research·2017
Same author

Utility and safety of tolvaptan in cirrhotic patients with hyponatremia: A prospective cohort study.

Annals of hepatology·2017

Related Experiment Video

Updated: May 29, 2025

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

523

Deep learning and machine learning in CT-based COPD diagnosis: Systematic review and meta-analysis.

Qian Wu1, Hui Guo1, Ruihan Li1

  • 1Department of Medical Imaging Center, The Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjian 830000, China.

International Journal of Medical Informatics
|February 1, 2025
PubMed
Summary

Artificial intelligence (AI) models show high accuracy in diagnosing chronic obstructive pulmonary disease (COPD) using CT scans. Both deep learning (DL) and machine learning (ML) models demonstrate comparable diagnostic efficacy, with potential for DL models with multiple-instance learning (MIL) to improve performance.

Keywords:
Artificial IntelligenceChronic Obstructive Pulmonary DiseaseDeep LearningDiagnoseMachine LearningSystematic review

More Related Videos

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.1K
Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.4K

Related Experiment Videos

Last Updated: May 29, 2025

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

523
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.1K
Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.4K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence in Medicine
  • Pulmonology

Background:

  • Chronic obstructive pulmonary disease (COPD) is a major global health challenge.
  • Artificial intelligence (AI) shows promise in improving COPD diagnosis through CT imaging.
  • Comprehensive evidence on the diagnostic performance of AI models for COPD is still needed.

Purpose of the Study:

  • To quantitatively analyze the diagnostic performance of AI models in CT images for COPD.
  • To provide evidence for the development of AI-driven COPD diagnostic tools.
  • To compare the efficacy of different AI approaches in COPD diagnosis.

Main Methods:

  • Systematic literature search of PubMed, Cochrane Library, Web of Science, and Embase up to September 1, 2024.
  • Quality assessment of included studies using the QUADAS-2 tool.
  • Meta-analysis of sensitivity, specificity, and area under the curve (AUC) using Stata18, RevMan 5.4, and Meta-Disc 1.4, including SROC curve plotting.

Main Results:

  • Meta-analysis included 15 studies with 22,817 patients, evaluating deep learning (DL), machine learning (ML), and DL with multiple-instance learning (MIL) models.
  • Pooled sensitivity was 86% (95% CI 78-91%), specificity 87% (95% CI 83-91%), and AUC 93% (95% CI 90-95%) for all AI models.
  • No significant difference in diagnostic efficacy was found between DL and ML models; DL with MIL showed a trend towards improved performance, though not statistically significant.

Conclusions:

  • Both DL and ML models demonstrate high accuracy for diagnosing COPD from CT images.
  • There is no significant difference in diagnostic efficacy between DL and ML models.
  • The multiple-instance learning (MIL) mechanism may enhance the performance of DL models in COPD diagnosis.