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

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

16.8K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
16.8K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

704
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
704
Prediction Intervals01:03

Prediction Intervals

2.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.4K

You might also read

Related Articles

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

Sort by
Same author

A hybrid deep learning model approach for automated detection and classification of cassava leaf diseases.

Scientific reports·2025
Same author

COVID-19 identification in chest X-ray images using intelligent multi-level classification scenario.

Computers & electrical engineering : an international journal·2022
Same author

Experimental data on the properties of natural fiber particle reinforced polymer composite material.

Data in brief·2017
Same author

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

Computational intelligence and neuroscience·2017
Same author

Shifting from presumptive to test-based management of malaria - technical basis and implications for malaria control in Ghana.

Ghana medical journal·2015
Same author

Epiphytic microorganisms and IAA synthesis.

Planta·2014
Same journal

A Multi-Head Attention Transformer Model for Wearable in Situ Fall Detection.

IEEE access : practical innovations, open solutions·2026
Same journal

Validating Single-Camera Pose Estimation Against Multi-Camera Motion Capture for Accessible Biomechanical Assessment.

IEEE access : practical innovations, open solutions·2026
Same journal

Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification.

IEEE access : practical innovations, open solutions·2026
Same journal

Radio-Frequency Toroid Susceptometry of Magnetic Nanoparticles: What Goes Around Comes Around.

IEEE access : practical innovations, open solutions·2026
Same journal

Cross-Architecture Knowledge Distillation for Histopathological Image Analysis.

IEEE access : practical innovations, open solutions·2026
Same journal

Mislabel Identification Using Transfer Learning-Based Ensemble Method.

IEEE access : practical innovations, open solutions·2026
See all related articles

Related Experiment Video

Updated: Oct 13, 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

961

Prediction of COVID-19 Using Genetic Deep Learning Convolutional Neural Network (GDCNN).

R G Babukarthik1, V Ananth Krishna Adiga1, G Sambasivam2

  • 1Department of Computer Science and EngineeringDayananda Sagar University Bengaluru 560078 India.

IEEE Access : Practical Innovations, Open Solutions
|November 17, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a Genetic Deep Learning Convolutional Neural Network (GDCNN) for diagnosing COVID-19 pneumonia from Chest X-rays (CXRs). The novel GDCNN model achieves high accuracy, aiding in rapid and precise disease identification.

Keywords:
Artificial Intelligence (AI)Chest X-Ray (CXR)Computed Tomography (CT)Genetic Deep Learning Convolutional Neural Network (GDCNN)

More Related Videos

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.2K
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

1.8K

Related Experiment Videos

Last Updated: Oct 13, 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

961
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.2K
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

1.8K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Pneumonia Diagnosis

Background:

  • Coronavirus disease (COVID-19) rapid spread causes severe pneumonia, impacting healthcare systems.
  • Early diagnosis of COVID-19 pneumonia is crucial for effective treatment and reducing healthcare burden.
  • Chest X-ray (CXR) is a widely accessible, rapid, and cost-effective imaging modality for pneumonia diagnosis.

Purpose of the Study:

  • To develop and evaluate a deep learning model for accurate COVID-19 pneumonia detection using CXR images.
  • To compare the performance of the proposed model against established transfer learning techniques.
  • To provide a reliable tool for differentiating COVID-19 pneumonia from normal lung conditions.

Main Methods:

  • Utilized a Genetic Deep Learning Convolutional Neural Network (GDCNN) trained from scratch.
  • Employed a dataset of over 5000 CXR images for training and classification.
  • Compared GDCNN performance against models like ReseNet18, ReseNet50, Squeezenet, DenseNet-121, and VGG16.

Main Results:

  • Achieved a classification accuracy of 98.84% for COVID-19 prediction.
  • Demonstrated high performance metrics: 93% precision, 100% sensitivity, and 97.0% specificity.
  • The GDCNN model outperformed existing transfer learning techniques in identifying COVID-19 pneumonia.

Conclusions:

  • The novel GDCNN model offers a highly accurate and efficient method for COVID-19 pneumonia detection via CXR.
  • The proposed approach shows superior performance in an unbalanced dataset environment.
  • This research contributes a valuable tool for early and precise COVID-19 diagnosis, alleviating healthcare system pressure.