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 Experiment Video

Updated: Oct 6, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.7K

Research on Chest Disease Recognition Based on Deep Hierarchical Learning Algorithm.

Lingling Li1, Yangyang Long2, Bangtong Huang3

  • 1Department of Central Laboratory, Children's Hospital of Shanghai Jiao Tong University, Shanghai, China.

Journal of Healthcare Engineering
|January 17, 2022
PubMed
Summary

Related Concept Videos

Classification of Illness01:17

Classification of Illness

8.1K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.1K
Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

67
Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
67
Angina II: Classification01:27

Angina II: Classification

52
Angina, also known as angina pectoris, is a chest pain resulting from diminished blood flow to the heart muscle and is often a symptom of coronary artery disease. Angina presents several variants with distinctive attributes, etiologies, and therapeutic approaches. The main types of angina include stable, unstable, variant (Prinzmetal's), microvascular, intractable, and silent ischemia.Stable angina is caused by atherosclerosis, which leads to the formation of plaques that narrow the coronary...
52
Coronary Artery Disease I: Introduction01:30

Coronary Artery Disease I: Introduction

279
Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
279
Cardiomyopathy III: Hypertrophic Cardiomyopathy01:29

Cardiomyopathy III: Hypertrophic Cardiomyopathy

84
Hypertrophic cardiomyopathy, or HCM, is an autosomal dominant genetic disorder characterized by asymmetric left ventricular hypertrophy without ventricular dilation. It is more common in men and is typically diagnosed in young, athletic adults.EtiologyHCM is primarily genetic and is caused by mutations in genes encoding sarcomeric proteins. Researchers have identified over 1400 mutations across at least 11 different genes. Among these, the most frequently occurring mutations are found in the...
84
Cardiomyopathy I: Introduction and Classification01:25

Cardiomyopathy I: Introduction and Classification

110
Cardiomyopathy, or CMP, is a group of diseases affecting the myocardial structure, impairing its ability to pump blood effectively. This condition can lead to arrhythmias, heart failure, or sudden cardiac death.Cardiomyopathies are classified into primary and secondary categories:Primary Cardiomyopathy refers to conditions involving only the heart muscle that are often idiopathic (of unknown cause) or genetic. They primarily affect the myocardium without the involvement of other systemic...
110

You might also read

Related Articles

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

Sort by
Same author

Advancing low-carbon additive manufacturing: an integrated deep learning approach for optimal resource and capacity management.

Scientific reports·2026
Same author

Zeolite-seed-directed Ru nanoparticles highly resistant against sintering for efficient nitrogen activation to ammonia.

Science bulletin·2023
Same author

Clinical outcomes of vinorelbine loading CalliSpheres beads in the treatment of previously treated advanced lung cancer with progressive refractory obstructive atelectasis.

Frontiers in bioengineering and biotechnology·2023
Same author

Coaching Leadership and Employees' Deviant Innovation Behavior: Mediation and Chain Mediation of Interactional Justice and Organizational Identification.

Psychology research and behavior management·2023
Same author

Relationship between vitamin D status and cardiac autonomic neuropathy in prediabetes.

Asia Pacific journal of clinical nutrition·2022
Same author

Association Between Coronary Artery Calcium Score and Bone Mineral Density in Type 2 Diabetes Mellitus with Different Visceral Fat Area.

Diabetes, metabolic syndrome and obesity : targets and therapy·2022
Same journal

RETRACTION: An IoMT-Based Approach for Real-Time Monitoring Using Wearable Neuro-Sensors.

Journal of healthcare engineering·2026
Same journal

RETRACTION: Learning to Discriminate Adversarial Examples by Sensitivity Inconsistency in IoHT Systems.

Journal of healthcare engineering·2026
Same journal

RETRACTION: Multi-Chaos-Based Lightweight Image Encryption-Compression for Secure Occupancy Monitoring.

Journal of healthcare engineering·2026
Same journal

RETRACTION: Image Risk Assessment of the Thyroid Cancer Model Based on Discriminant Analysis and the Value of TAP and CEA Combined Detection.

Journal of healthcare engineering·2026
Same journal

RETRACTION: Meta-Analysis of the Prognostic Value of Narcotrend Monitoring of Different Depths of Anesthesia and Different Bispectral Index (BIS) Values for Cognitive Dysfunction after Tumor Surgery in Elderly Patients.

Journal of healthcare engineering·2026
Same journal

Correction to "Representation of Differential Learning Method for Mitosis Detection".

Journal of healthcare engineering·2026
See all related articles
This summary is machine-generated.

This study introduces SGGCN, an efficient deep learning model for chest X-ray analysis, improving diagnostic speed and accuracy for lung and heart diseases. It balances computational efficiency with performance, making advanced diagnostics more accessible.

Area of Science:

  • Medical Imaging and Radiology
  • Artificial Intelligence in Healthcare
  • Deep Learning for Medical Diagnostics

Background:

  • Chest X-rays are crucial for diagnosing cardiopathy and lung diseases, but manual analysis is time-consuming.
  • Traditional classification methods struggle with correlated and hierarchical disease features.
  • Existing deep learning models, especially Graph Convolutional Network (GCN)-based ones, require high computational resources.

Purpose of the Study:

  • To develop an efficient deep learning model for rapid and accurate chest X-ray analysis.
  • To address the computational cost limitations of current GCN-based diagnostic systems.
  • To improve the detection of correlated and hierarchical features in chest X-rays.

Main Methods:

  • Proposed SGGCN, an efficient convolutional neural network integrated with GCN.

More Related Videos

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 6, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

2.7K
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
  • Utilized SGNet-101 with ShuffleGhost Blocks as a lightweight backbone for feature extraction.
  • Introduced a novel GCN module (GCNM) to efficiently combine multi-layer hierarchical features.

    • Main Results:

    • SGGCN achieved a test AUC of 0.7831 on the CheXPert dataset.
    • Demonstrated significant reductions in parameters (1.2M, -73.73%) and FLOPs (3.1B, -80.82%) compared to ResNet-101 backbone GCN models.
    • Outperformed GCN with MobileNet backbone in terms of accuracy while maintaining efficiency.

    Conclusions:

    • SGGCN offers a computationally efficient solution for chest X-ray diagnostics.
    • The model effectively extracts hierarchical disease features using an optimized GCN architecture.
    • SGGCN provides a viable alternative for scenarios requiring fast predictions and limited computational resources.