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

Pulmonary Tuberculosis IV01:26

Pulmonary Tuberculosis IV

459
Tuberculosis, more commonly referred to as TB, is an infectious disease stemming from Mycobacterium tuberculosis. While it primarily impacts the lungs, TB can also affect other body areas. Given its severity and global impact, timely and accurate diagnosis is crucial for controlling its spread and improving patient outcomes.
Several diagnostic approaches are used to detect TB. The conventional method is the Tuberculin Skin Test (TST), also known as the Mantoux test. However, this method has...
459
Pleural Effusion I: Introduction01:25

Pleural Effusion I: Introduction

3.7K
Pleural effusion is an abnormal fluid accumulation in the pleural cavity, a narrow space between the lungs and the chest wall. It is not a disease per se but rather a symptom or indication of an underlying disease. In normal circumstances, this space contains a small amount of fluid (5 to 15 mL), a lubricant facilitating the non-frictional movement of the pleural surfaces.
There are two main types of pleural effusion: transudative and exudative. They are differentiated using Light's...
3.7K
Pleural Effusion II: Symptoms and Management01:28

Pleural Effusion II: Symptoms and Management

585
Pleural Effusion Overview
A pleural effusion is the abnormal collection of fluid between the parietal and visceral pleura layers of tissue that form the lining of the lungs and chest cavity. It can occur independently or due to surrounding parenchymal diseases, such as infection, malignancy, or inflammatory conditions.
Clinical Manifestations:
585
Pulmonary Tuberculosis II01:28

Pulmonary Tuberculosis II

1.3K
Tuberculosis, or TB, is a bacterial infectious disease caused by Mycobacterium tuberculosis. While its primary impact is on the lungs, leading to pulmonary tuberculosis, it can also affect various other organs, a condition referred to as extrapulmonary tuberculosis.
Here is a detailed explanation of its pathophysiology:
Transmission: The process begins when a person inhales droplet nuclei containing M. tuberculosis. These are typically released into the air when an individual with pulmonary or...
1.3K
Pulmonary Tuberculosis III01:31

Pulmonary Tuberculosis III

872
Tuberculosis (TB) is a contagious infection primarily affecting the lung parenchyma but which can also affect other body parts. TB can be classified based on disease development, presentation, and the affected anatomical site.
The first classification is based on the development of the disease, and it includes the following categories:
872

You might also read

Related Articles

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

Sort by
Same author

Radiation cross-linked collagen/dextran dermal scaffolds: effects of dextran on cross-linking and degradation.

Journal of biomaterials science. Polymer edition·2014
Same author

Hexagonal Ag nanoarrays induced enhancement of blue light emission from amorphous oxidized silicon nitride via localized surface plasmon coupling.

Optics express·2014
Same author

The gene expression patterns of BMPR2, EP300, TGFβ2, and TNFAIP3 in B-Lymphoma cells.

Cancer biology & medicine·2014
Same author

[Therapeutic effect of vildagliptin and insulin aspart injection in elderly patients with type 2 diabetes].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University·2014
Same author

[Evaluation and indication of human epithelial growth factor receptor 2 status in breast carcinoma with amplified chromosome].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences·2014
Same author

Thiol-assisted one-pot synthesis of peptide/protein C-terminal thioacids from peptide/protein hydrazides at neutral conditions.

Organic & biomolecular chemistry·2014
Same journal

Depemokimab: toward biannual biologic therapy for severe eosinophilic asthma.

Respiratory research·2026
Same journal

Precision treatment of COPD based on novel imaging phenotypes: a treatable traits approach.

Respiratory research·2026
Same journal

Lung organoids and organ-on-a-chip models in respiratory disease research: advances, applications, and challenges.

Respiratory research·2026
Same journal

Immune-related adverse event profiles and survival outcomes in non-small cell lung cancer: a cluster analysis from a long-term real-world study.

Respiratory research·2026
Same journal

Real-time algorithm-driven ventilation feedback to improve lung-protective ventilation in patients with ARDS (REALVENT-study): study protocol for a multicentre randomised controlled trial.

Respiratory research·2026
Same journal

Identification and functional validation of lactylation-related hub genes in idiopathic pulmonary fibrosis based on multi-omics analysis.

Respiratory research·2026
See all related articles

Related Experiment Video

Updated: Jan 5, 2026

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

2.0K

Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms.

Zenghua Ren1, Yudan Hu1, Ling Xu2

  • 1Department of Respiratory Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, YiShan Road, Shanghai, 200233, China.

Respiratory Research
|October 18, 2019
PubMed
Summary
This summary is machine-generated.

A new random forest (RF) model using artificial intelligence (AI) effectively diagnoses tuberculous pleural effusion (TPE). This AI-driven approach offers a more accurate and efficient method for identifying TPE compared to traditional diagnostics.

Keywords:
Artificial intelligenceDiagnostic modelMachine learning algorithmTuberculous pleural effusion

More Related Videos

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.6K
Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

387

Related Experiment Videos

Last Updated: Jan 5, 2026

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

2.0K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.6K
Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

387

Area of Science:

  • Medical Informatics
  • Pulmonology
  • Machine Learning in Medicine

Background:

  • Diagnosing tuberculous pleural effusion (TPE) presents significant challenges.
  • Artificial intelligence (AI) and machine learning algorithms (MLAs) offer enhanced efficiency, objectivity, and accuracy in disease diagnosis.

Purpose of the Study:

  • To develop and evaluate machine learning algorithms for the differential diagnosis of tuberculous pleural effusion (TPE).
  • To compare the diagnostic performance of MLA models against pleural fluid adenosine deaminase (pfADA).

Main Methods:

  • Retrospective collection of data from 192 TPE, 54 parapneumonic pleural effusion (PPE), and 197 malignant pleural effusion (MPE) cases.
  • Development of TPE diagnostic models using logistic regression, k-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF) based on 28 features.
  • Design of a refined RF model using 12 key features and validation through a prospective study.

Main Results:

  • The RF model demonstrated superior diagnostic performance (sensitivity 89.1%, specificity 93.6%) compared to other MLAs and pfADA (sensitivity 85.4%, specificity 84.1%).
  • The refined RF model achieved high sensitivity (90.6%) and specificity (92.3%) in the initial evaluation.
  • Prospective validation of the refined RF model showed excellent sensitivity (100.0%) and specificity (90.0%) for TPE diagnosis.

Conclusions:

  • A random forest (RF) model provides a highly effective, economical, and rapid method for diagnosing TPE.
  • This AI-driven approach can significantly improve the clinical diagnosis and management of TPE.