Jove
Visualize
Contact Us

Related Concept Videos

Pneumonia III: Complications and Assessment01:30

Pneumonia III: Complications and Assessment

202
Pneumonia poses the potential for numerous complications that warrant consideration. These complications include the following:
202
Pneumonia IV: Management01:28

Pneumonia IV: Management

322
The treatment of pneumonia varies based on its severity and the causative pathogen. Here is a structured approach to managing pneumonia, integrating pharmaceutical and supportive care strategies.
Bacterial Pneumonia Treatment
For bacterial pneumonia, antibiotics serve as the cornerstone of therapy. Initial treatment often begins with empirical antibiotics, tailored to the anticipated causative organism and adjusted based on culture results. Key antibiotic choices include:
322
Pneumonia I: Introduction01:30

Pneumonia I: Introduction

221
Pneumonia is an acute respiratory infection that targets the lungs, specifically the alveoli. These tiny air sacs, essential for oxygen exchange, become engorged with pus and fluid, severely hindering breathing, decreasing oxygen absorption, and causing significant pain and discomfort during respiration.
Risk Factors
Various factors influence the likelihood of developing pneumonia. Age plays a crucial role, with infants, children under two, and individuals over 65 at increased risk due to their...
221

You might also read

Related Articles

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

Sort by
Same author

Large language model biases in health care: a scoping review and call for an integrated assessment framework.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Correlation Aware Relevance-Based Semantic Index for Clinical Big Data Repository.

Journal of imaging informatics in medicine·2024
See all related articles
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 Experiment Video

Updated: Jun 25, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

736

Texture-Based Classification to Overcome Uncertainty between COVID-19 and Viral Pneumonia Using Machine Learning and

Omar Farghaly1, Priya Deshpande1

  • 1Data-Intensive Computing Distributed Systems Laboratory, Department of Electrical and Computer Engineering, Marquette University, Milwaukee, WI 53233, USA.

Diagnostics (Basel, Switzerland)
|May 24, 2024
PubMed
Summary
This summary is machine-generated.

A new AI model accurately classifies chest X-rays for COVID-19 and pneumonia using advanced texture analysis and deep learning. This approach improves diagnostic accuracy, especially for complex cases, outperforming traditional methods.

Keywords:
COVID-19classificationdeep learningmachine learningtexture-based featuresviral pneumonia

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: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K

Related Experiment Videos

Last Updated: Jun 25, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

736
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: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Computational Biology

Background:

  • COVID-19 symptoms mimic viral pneumonia, complicating early diagnosis.
  • Accurate classification of COVID-19 is challenging due to high-dimensional image data and limitations of previous studies.
  • Young individuals, the elderly, and immunocompromised populations are particularly vulnerable.

Purpose of the Study:

  • To develop a novel classification model for accurate chest X-ray image analysis.
  • To differentiate between normal, COVID-19, and viral pneumonia cases.
  • To overcome limitations of previous studies using simplistic algorithms and small datasets.

Main Methods:

  • Integration of advanced texture feature extraction methods: Gray-Level Co-occurrence Matrix (GLCM), Gray-Level Dependence Matrix (GLDM), and wavelet transform.
  • Application within a deep learning framework for image classification.
  • Leveraging unique texture characteristics inherent to each dataset class.

Main Results:

  • Superior classification performance compared to traditional methods.
  • High accuracy (DLNN: 0.92), recall (DLNN: 0.93), precision (DLNN: 0.87), and F1-Score (DLNN: 0.89) achieved by the deep learning neural network (DLNN).
  • Demonstrated effectiveness even with complex and diverse image data.

Conclusions:

  • The proposed model represents a significant advancement in AI-based diagnostic systems for COVID-19 and pneumonia.
  • The approach offers improved patient outcomes and healthcare management strategies.
  • Advanced texture analysis combined with deep learning enhances diagnostic capabilities for respiratory illnesses.