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: Jun 17, 2026

Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality
07:46

Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality

Published on: August 9, 2024

Training an Artificial Intelligence Model for Aortic Dissection Detection Using Non-Contrast Computed Tomography

Yi Gao1, Liu Siyu2, Yirui Jiang2

  • 1Department of Cardiology, China-Japan Union Hospital of Jilin University.

Journal of Visualized Experiments : Jove
|June 15, 2026
PubMed
Summary

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

Ethanol Infusion Into the Vein of Marshall for Atrial Fibrillation: Clinical Efficacy and Technical Limitations.

Clinical cardiology·2026
Same author

PD-1/PD-L1 immune checkpoint inhibitors in Hodgkin lymphoma: A meta- and network meta-analysis.

Translational oncology·2026
Same author

Schistosoma japonicum histone acetyltransferase 1 (SjHAT1): A novel anti-schistosomal drug target.

PLoS pathogens·2026
Same author

A reporting checklist for large language models in behavioural science.

Nature human behaviour·2026
Same author

Low-Density and Flexible Silicone with Tunable Transparency for Thermal Insulation and Passive Cooling.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

CircCDK6 Regulates Stemness Maintenance and Cisplatin Resistance in Lung Adenocarcinoma via the Wnt/β-Catenin Signaling Pathway.

Cancer management and research·2026
Same journal

A Video Protocol of a Randomized Controlled Clinical Trial - Electrochemotherapy of Cutaneous Metastases with Reduced Dose Bleomycin (BLESS Trial).

Journal of visualized experiments : JoVE·2026
Same journal

A Standardized Ex Vivo Porcine Oromucosal Model for Evaluating Peptide Fluxes.

Journal of visualized experiments : JoVE·2026
Same journal

Lightweight English Text Classification with Deep Learning Based on Complex System Theory.

Journal of visualized experiments : JoVE·2026
Same journal

Integrating Artificial Intelligence-Assisted Translation Support into English Courses: Effects on Translation Accuracy, Perceived Stress, and Anxiety.

Journal of visualized experiments : JoVE·2026
Same journal

A Toxin-Based Counter-Selection System for Markerless Gene Deletion and High-Density Tn5 Transposon Mutagenesis in Pectobacterium brasiliense.

Journal of visualized experiments : JoVE·2026
Same journal

Seamless Multimodal Human-Robot Communication: Integration Techniques in Human-Computer Interaction.

Journal of visualized experiments : JoVE·2026
See all related articles
This summary is machine-generated.

This study introduces an artificial intelligence model for identifying aortic dissection (AD) using non-contrast CT scans. The AI tool offers rapid screening, improving early detection of this critical vascular condition.

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Cardiovascular Disease

Background:

  • Aortic dissection (AD) is a life-threatening condition requiring prompt diagnosis.
  • Current diagnostic methods can be time-consuming, delaying critical treatment.
  • There is a clinical need for faster, more accessible AD identification tools.

Purpose of the Study:

  • To develop and validate an artificial intelligence (AI)-based model for identifying aortic dissection (AD).
  • To utilize non-contrast computed tomography (CT) for AD detection.
  • To create an accessible tool for preliminary AD screening.

Main Methods:

  • Collected chest CT and aortic CT angiography datasets from AD and non-AD patients.
  • Manually segmented and annotated vascular structures on axial images using LabelMe software.

Related Experiment Videos

Last Updated: Jun 17, 2026

Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality
07:46

Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality

Published on: August 9, 2024

  • Developed and validated an AI model using an 8:1:1 training, test, and validation data split.

    • Main Results:

    • Successfully developed an AI model with robust detection performance for AD.
    • Established an online platform for effective visualization and presentation of results.
    • Demonstrated the model's capability for rapid, preliminary screening of AD.

    Conclusions:

    • The developed AI model offers a powerful and intelligent solution for AD identification.
    • This approach addresses the unmet clinical need for accessible early detection of aortic dissection.
    • The AI tool can aid in rapid preliminary screening across various clinical settings.