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

Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

Radiological Investigation III: Pulmonary Angiogram and PET Scan

171
Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...
171
Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

428
Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
428
Pulmonary Tuberculosis I01:29

Pulmonary Tuberculosis I

332
Tuberculosis, often called TB, is a contagious illness primarily caused by Mycobacterium tuberculosis. It mainly affects the lung parenchyma but can also impact other body parts.
Causative Organism
The primary infectious agent causing tuberculosis is Mycobacterium tuberculosis, a slow-growing, acid-fast, aerobic rod that exhibits sensitivity to heat and ultraviolet light. Instances of Mycobacterium bovis and Mycobacterium avium contributing to the development of TB infection are rare.
Mode of...
332
Pulmonary Tuberculosis V01:28

Pulmonary Tuberculosis V

246
Medical management of tuberculosis (TB) patients involves a comprehensive approach that includes diagnosis, treatment, and monitoring. The specific strategies can vary depending on the type of tuberculosis (latent or active), the patient's overall health status, and other considerations.
Latent tuberculosis infection occurs when TB bacteria are present in a person's body, but are not causing illness or symptoms. It is not contagious, and preventive treatment is crucial to avoid the...
246
Pulmonary Tuberculosis III01:31

Pulmonary Tuberculosis III

452
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:
452
Pulmonary Tuberculosis II01:28

Pulmonary Tuberculosis II

381
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...
381

You might also read

Related Articles

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

Sort by
Same author

Research trends in educational interventions for digital sexual media literacy among adolescents: a scoping review (2015-2025).

Women's health nursing (Seoul, Korea)·2026
Same author

Factors Associated With Preoperative Radiological Tumor Size Underestimation in Clinical T1-2 Breast Cancer Patients.

The breast journal·2026
Same author

Asymmetric Safety Corridors for Free-Hand S2-Alar-Iliac Screw Placement: Quantifying Direction-Specific Tolerance Around Patient-Specific Optimal Trajectories.

Journal of clinical medicine·2026
Same author

Hybrid Dissolving Microneedles Incorporating Hyaluronic Acid Microdepots for Pain-free and Long-acting Corticosteroid Therapy.

Biomaterials research·2026
Same author

Functional Pathological Features and Molecular Markers in Alzheimer's Disease.

International journal of molecular sciences·2026
Same author

The Central Role of Neuronal Cell Death in Alzheimer's Disease Pathobiology.

Biomedicines·2026

Related Experiment Video

Updated: Sep 17, 2025

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.1K

Multimodal Generative Artificial Intelligence Model for Creating Radiology Reports for Chest Radiographs in Patients

Eun Kyoung Hong1, Hae Won Kim2, Ok Kyu Song1

  • 1Department of Radiology, Mass General Brigham, Brigham & Women's Hospital, 75 Francis St, Boston, MA 02115.

AJR. American Journal of Roentgenology
|July 2, 2025
PubMed
Summary

A new generative artificial intelligence (AI) model shows potential for tuberculosis screening by generating chest radiograph reports. However, the AI model requires human oversight due to its lower standalone diagnostic accuracy compared to radiologists.

Keywords:
artificial intelligencechest radiographgenerative AItuberculosis

More Related Videos

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

1.6K
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

14.3K

Related Experiment Videos

Last Updated: Sep 17, 2025

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.1K
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

1.6K
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

14.3K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Public Health

Background:

  • Chest radiography is vital for tuberculosis screening in high-prevalence areas.
  • Limited medical resources in some regions hinder expert radiologist availability for widespread screening.

Purpose of the Study:

  • To assess a multimodal generative artificial intelligence (AI) model for detecting tuberculosis-associated abnormalities on chest radiographs.
  • To evaluate the AI model's performance in tuberculosis screening.

Main Methods:

  • Retrospective analysis of 800 chest radiographs from tuberculosis screening programs.
  • A generative AI model produced free-text reports for radiographs.
  • Radiologists reviewed radiographs with and without AI reports to assess diagnostic performance and report acceptance.

Main Results:

  • The AI model achieved 90.8% accuracy in detecting tuberculosis-related abnormalities.
  • Radiologists' accuracy improved when using AI-generated reports, though standalone AI performance was lower than human readers.
  • Localization performance of the AI model was significantly lower than that of radiologists.

Conclusions:

  • Generative AI reports can augment radiologists' assessments but require human oversight due to current performance limitations.
  • The AI model holds potential for tuberculosis screening in underserved regions, pending technical improvements.