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

Self-Concept01:19

Self-Concept

1.7K
Self-concept is the cognitive and emotional understanding individuals hold about their identity. It evolves through various developmental stages, beginning in infancy and maturing as children grow. This concept influences how individuals perceive their abilities, interact with others, and manage challenges throughout life.
Infancy and Emerging Recognition
During infancy, self-concept is virtually nonexistent. Babies do not distinguish themselves as separate entities and often mistake their...
1.7K
Fineness of Cement01:15

Fineness of Cement

518
The fineness of cement directly influences the rate of hydration, as the hydration begins at the surface of the cement particles. In addition to hydration, the fineness of cement is vital for various properties of concrete including workability, gypsum requirement, and long-term behavior. The fineness of cement is represented in terms of the specific surface of cement which is typically measured in square meters per kilogram, with several methods available for this determination.
Direct...
518
Fineness Modulus01:19

Fineness Modulus

1.5K
The fineness modulus (FM) of aggregate is a numerical index that measures the coarseness or fineness of the particles. It is calculated by adding the cumulative percentages of aggregate retained on each of a specified series of sieves and dividing the sum by 100.
Consider performing sieve analysis on sand through a set of ASTM sieves. The weight of aggregate retained in each sieve and pan placed at the bottom is recorded, as given in Column B of Table 1.
To determine the fineness modulus of...
1.5K
Lung Capacity01:47

Lung Capacity

56.3K
The air in the lungs is measured in volumes and capacities. Lung volume measures reflect the amount of air taken in, released, or left over after a lung function, like a single inhalation. Lung capacity measures are sums of two or more lung volume measures.
56.3K
Concepts and Prototypes01:24

Concepts and Prototypes

548
The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
548
Endoscopic Studies I: Bronchoscopy and Thoracoscopy01:30

Endoscopic Studies I: Bronchoscopy and Thoracoscopy

622
Endoscopy is a non-surgical medical technique used to examine a person's internal organs and vessels. This lesson will focus on two types of endoscopic studies: bronchoscopy and thoracoscopy.
Bronchoscopy
Description
Bronchoscopy is a procedure that involves direct visualization of the larynx, trachea, and bronchi for diagnostic and therapeutic purposes. A flexible fiber optic or rigid bronchoscope is used to carry out the procedure. The fiber-optic bronchoscope is more frequently used due...
622

You might also read

Related Articles

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

Sort by
Same author

Rewiring Metal-Dependent Cell Death to Unlock Immunotherapy in Colorectal Cancer.

Nano letters·2026
Same author

Efficacy and safety of GLP-1 receptor agonists for adolescents and children with obesity: a meta-analysis of randomized controlled trials.

BMC endocrine disorders·2026
Same author

Serum high-density lipoprotein partially mediates the inverted L-shaped association between estimated glucose disposal rate and risk of kidney stones: A cross-sectional study from National Health and Nutrition Examination Survey.

The Journal of international medical research·2026
Same author

Precision Synthesis of Symmetrical Stellated Icosahedrons for Tailored Plasmonics and Magnetic Assembly.

ACS nano·2026
Same author

AI knowledge, attitudes, perceptions, and willingness to use AI among oncologists in China: a nationwide cross-sectional study.

BMC medical education·2026
Same author

Hierarchical Reconfigurable Metasurface Based on Scenario-Guided Functional Modules and Programmable Core.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Related Experiment Video

Updated: Feb 3, 2026

Author Spotlight: Expanding Interventional Pulmonology Research with Robotic-Assisted Bronchoscopy
04:10

Author Spotlight: Expanding Interventional Pulmonology Research with Robotic-Assisted Bronchoscopy

Published on: July 19, 2024

1.3K

Optimize Transfer Learning for Lung Diseases in Bronchoscopy Using a New Concept: Sequential Fine-Tuning.

Tao Tan1,2, Zhang Li3, Haixia Liu4

  • 1Department of Biomedical EngineeringEindhoven University of Technology5600 MBEindhovenThe Netherlands.

IEEE Journal of Translational Engineering in Health and Medicine
|October 17, 2018
PubMed
Summary

A novel computer-aided diagnosis (CAD) system using sequential fine-tuning (SFT) improves lung disease detection during bronchoscopy. This AI tool enhances diagnostic accuracy for lung cancer and tuberculosis (TB), aiding selective biopsies.

Keywords:
BronchoscopyDenseNetcomputer-aided diagnosisdeep learninglung cancersequential fine-tuningtransfer learningtuberculosis

More Related Videos

Author Spotlight: Unveiling Neural Mechanisms Through Automated Evaluation of Motor Learning and Myelin Plasticity Studies Using the Erasmus Ladder
08:51

Author Spotlight: Unveiling Neural Mechanisms Through Automated Evaluation of Motor Learning and Myelin Plasticity Studies Using the Erasmus Ladder

Published on: December 15, 2023

2.1K
Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting
04:47

Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting

Published on: June 23, 2023

3.5K

Related Experiment Videos

Last Updated: Feb 3, 2026

Author Spotlight: Expanding Interventional Pulmonology Research with Robotic-Assisted Bronchoscopy
04:10

Author Spotlight: Expanding Interventional Pulmonology Research with Robotic-Assisted Bronchoscopy

Published on: July 19, 2024

1.3K
Author Spotlight: Unveiling Neural Mechanisms Through Automated Evaluation of Motor Learning and Myelin Plasticity Studies Using the Erasmus Ladder
08:51

Author Spotlight: Unveiling Neural Mechanisms Through Automated Evaluation of Motor Learning and Myelin Plasticity Studies Using the Erasmus Ladder

Published on: December 15, 2023

2.1K
Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting
04:47

Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting

Published on: June 23, 2023

3.5K

Area of Science:

  • Medical Imaging and Diagnostics
  • Artificial Intelligence in Medicine
  • Pulmonology

Background:

  • Bronchoscopy is crucial for lung disease diagnosis, often requiring immediate biopsy decisions.
  • Lung biopsies carry risks of uncontrollable bleeding, necessitating careful selection.
  • Accurate, real-time diagnostic support is needed to guide biopsy decisions during bronchoscopy.

Purpose of the Study:

  • To develop a computer-aided diagnosis (CAD) system to assist physicians in diagnosing lung diseases during bronchoscopy.
  • To improve the selectivity of lung biopsies by providing a second diagnostic opinion.
  • To enhance the accuracy of diagnosing lung cancers and tuberculosis (TB) via bronchoscopy.

Main Methods:

  • Proposed a novel transfer learning (TL) method called sequential fine-tuning (SFT) built upon the DenseNet architecture.
  • Evaluated the SFT method on a dataset comprising 81 normal cases, 76 TB cases, and 277 lung cancer cases.
  • Compared the performance of SFT against traditional fine-tuning (FT) methods for TL.

Main Results:

  • The SFT method achieved an overall accuracy of 82%, outperforming traditional TL methods (70-74%).
  • Specific detection accuracies for SFT were 87% for lung cancer, 54% for TB, and 91% for normal cases.
  • The CAD system demonstrated superior performance in differentiating between lung cancers, TB, and normal lung tissue.

Conclusions:

  • The developed CAD system, utilizing SFT, shows significant potential to improve diagnostic accuracy in bronchoscopy.
  • This AI-driven approach can aid clinicians in making more informed and selective biopsy decisions.
  • The system offers a valuable tool for enhancing the diagnosis and treatment planning for lung diseases.