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

You might also read

Related Articles

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

Sort by
Same author

Lanthanum-modulated hollow CuO nanofibers enable selective CO<sub>2</sub> electroreduction to multicarbon products at high current densities.

Journal of colloid and interface science·2026
Same author

Building a SHAP interpretable prediction model for stroke-associated pneumonia [stroke-associated pneumonia (SAP)] in patients with aneurysmal subarachnoid hemorrhage (aSAH).

Frontiers in neurology·2026
Same author

Pathogen distribution and prognostic risk factors in respiratory intensive care unit (RICU) patients of a large general hospital before and after COVID-19 pandemic.

Journal of thoracic disease·2025
Same author

Zinc Metalloprotease SlMEP1: An Essential Factor Required for Fungal Virulence in <i>Stemphylium lycopersici</i>.

Journal of fungi (Basel, Switzerland)·2025
Same author

Heterophily-Aware Representation Learning on Heterogeneous Graphs.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Creating Perforations in the Sclerotic Region of the Proximal Tibia During Total Knee Arthroplasty to Enhance Prosthesis Stability.

Orthopaedic surgery·2025
Same journal

Correction: Luca et al. Global and Regional Diagnostic Results of Progress Toward Cervical Cancer Elimination, According to the WHO Strategy: A Systematic Literature Review with Narrative Synthesis. <i>Diagnostics</i> 2026, <i>16</i>, 1224.

Diagnostics (Basel, Switzerland)·2026
Same journal

Association Between Systemic Inflammatory Response Biomarkers and Disease Activity in Systemic Lupus Erythematosus: A Multi-Center Retrospective Study.

Diagnostics (Basel, Switzerland)·2026
Same journal

Vertebrogenic Low Back Pain and Basivertebral Nerve Ablation: A Review of Mechanisms, Imaging-Driven Selection, and Clinical Outcomes.

Diagnostics (Basel, Switzerland)·2026
Same journal

Multivalvular Carcinoid Heart Disease: The Role of Echocardiography in Diagnosis and Selection for Heterotopic Bicaval Valve Implantation.

Diagnostics (Basel, Switzerland)·2026
Same journal

Data-Efficient and Explainable Multimodal Survival Prediction in NSCLC Using Deep Image Embeddings, Clinical Variables, and Gradient-Boosted Trees.

Diagnostics (Basel, Switzerland)·2026
Same journal

Anomalous Left Coronary Artery from the Pulmonary Artery: Cinematic Volume Rendering Technique for Enhanced Anatomic Visualization.

Diagnostics (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jun 23, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

Enhancing Medical Image Classification with an Advanced Feature Selection Algorithm: A Novel Approach to Improving

Abduljlil Abduljlil Ali Abduljlil Habeb1, Mundher Mohammed Taresh2, Jintang Li1

  • 1College of Computer Science and Electronic Engineering, Hunan University, Changsha 410012, China.

Diagnostics (Basel, Switzerland)
|June 19, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new method using a cuckoo search algorithm with Caputo fractional order for glaucoma classification. The technique improves diagnostic accuracy and efficiency for early detection of this vision-impairing condition.

Keywords:
Caputo fractional ordercuckoo searchfeature selectionglaucoma

More Related Videos

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.8K

Related Experiment Videos

Last Updated: Jun 23, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.8K

Area of Science:

  • Ophthalmology
  • Computer Science
  • Artificial Intelligence

Background:

  • Glaucoma is a leading cause of irreversible blindness, necessitating early detection and treatment.
  • Automated diagnostic tools are crucial for timely glaucoma identification and management.
  • Existing feature selection methods may face limitations like memory truncation in fractional order definitions.

Purpose of the Study:

  • To propose a novel feature selection method for enhanced glaucoma classification.
  • To address memory length truncation issues in Caputo fractional order definitions.
  • To improve the accuracy and efficiency of automated glaucoma detection systems.

Main Methods:

  • Developed a hybrid feature selection approach integrating the cuckoo search algorithm with Caputo fractional order (CFO-CS).
  • Addressed Caputo definition's memory length truncation using a fixed memory step and adjustable term count.
  • Combined multiple feature extraction techniques (HOGs, LBPs, deep features from MobileNet/VGG19) into a unified feature vector.
  • Employed data augmentation to increase training dataset size and diversity.
  • Evaluated feature selection using k-nearest neighbor and assessed classification performance.

Main Results:

  • The proposed CFO-CS method demonstrated improved convergence speed and optimal solution attainment during training.
  • Achieved high performance metrics on the test set: 92.62% accuracy, 94.70% precision, 93.52% F1-Score, 92.98% specificity, 92.36% sensitivity, and 85.00% Matthew's correlation coefficient.
  • The method proved effective in selecting informative features for glaucoma classification.

Conclusions:

  • The novel CFO-CS feature selection method significantly enhances glaucoma classification performance.
  • The technique offers a generalizable and applicable solution for automated ophthalmological diagnostics.
  • The study highlights the potential of fractional calculus and metaheuristic algorithms in medical image analysis.