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

Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

511
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
511
Variance01:15

Variance

12.5K
The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.
The standard deviation measures the spread in the same units as the data....
12.5K
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K
Lung Capacity01:47

Lung Capacity

56.4K
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.
56.4K

You might also read

Related Articles

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

Sort by
Same author

Hybrid deep learning with attention mechanism for monitoring and classifying physical exercise postures using sensor data.

Scientific reports·2026
Same author

SA-ConSinGAN and reservoir computing fusion for accurate bearing fault classification and severity identification using GAF-based techniques.

Scientific reports·2026
Same author

An Inverse Problem for a Fractional Space-Time Diffusion Equation with Fractional Boundary Condition.

Entropy (Basel, Switzerland)·2026
Same author

Evaluation of the Novel RITA MTBC Assay for Tuberculosis Detection: A Pilot Comparison with GeneXpert and BD MAX™.

Pathogens (Basel, Switzerland)·2026
Same author

Plasma cardiovascular stress biomarkers response to marathon running.

Sports medicine and health science·2026
Same author

Anatomical and Functional Outcomes of Sutureless Scleral-Fixated Carlevale Intraocular Lens Implantation: A Retrospective Study.

Journal of clinical medicine·2025

Related Experiment Video

Updated: Feb 9, 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

2.1K

Small lung nodules detection based on local variance analysis and probabilistic neural network.

Marcin Woźniak1, Dawid Połap1, Giacomo Capizzi1

  • 1Institute of Mathematics, Silesian University of Technology, Kaszubska 23, Gliwice 44-100, Poland; Department of Electric, Electronic and Informatics Engineering, University of Catania, Viale A. Doria 6, Catania 95125, Italy.

Computer Methods and Programs in Biomedicine
|June 2, 2018
PubMed
Summary

This study introduces an automated method for lung carcinoma detection using chest X-rays. The novel approach achieves 92% classification accuracy, aiding radiologists in accurate lung cancer diagnosis.

Keywords:
Automatic pathology recognitionBiomedical image processingChest X-ray screeningProbabilistic neural network

More Related Videos

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.3K
Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery
07:30

Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery

Published on: May 4, 2022

3.8K

Related Experiment Videos

Last Updated: Feb 9, 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

2.1K
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.3K
Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery
07:30

Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery

Published on: May 4, 2022

3.8K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Oncology

Background:

  • Chest X-rays are crucial for diagnosing lung diseases.
  • Interpreting lung nodules on X-rays can be challenging for radiologists.
  • Automated diagnostic tools can significantly improve medical analysis.

Purpose of the Study:

  • To develop a novel automated method for classifying lung carcinomas from chest X-rays.
  • To improve the accuracy and efficiency of lung nodule detection and classification.

Main Methods:

  • A new classification method for lung carcinomas is proposed.
  • Lung nodules are localized and extracted using local variance computation.
  • A probabilistic neural network (PNN) is employed for classifying true nodules from false positives.

Main Results:

  • The developed approach achieved 92% correct classifications.
  • The method demonstrated high sensitivity (95%) and specificity (89.7%).
  • Misclassification rates were low, with 6% false positives and 2% false negatives.

Conclusions:

  • The proposed method is a simple yet effective automated approach for lung nodule detection.
  • It successfully detects low-contrast nodules, overcoming limitations of existing algorithms.
  • A new PNN training algorithm reduces computational complexity while maintaining performance.