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

Graves Disease II: Pathophysiology01:24

Graves Disease II: Pathophysiology

Graves’ disease is an autoimmune disorder characterized by the production of thyroid-stimulating immunoglobulins (TSI) that activate TSH receptors, leading to excessive synthesis and release of thyroid hormones (T3 and T4) and resulting in hyperthyroidism.Among all causes of hyperthyroidism, Graves’ disease is the most common and can happen at any age, though it is more frequent in women. It produces a hypermetabolic state with features such as weight loss, tachycardia, tremor, and heat...

You might also read

Related Articles

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

Sort by
Same author

Genetic and transcriptomic determinants of disseminated coccidioidomycosis identify a founder variant in <i>NLRX1</i> and ancestry-specific rare variants in immune response genes.

medRxiv : the preprint server for health sciences·2026
Same author

Automated implementation of the SwabSeq COVID-19 diagnostic assay on the opentrons flex liquid-handling robot.

Diagnostic microbiology and infectious disease·2026
Same author

Single-cell profiling of DNA methylation in autism spectrum disorder prefrontal cortex reveals distinct regulatory and aging signatures.

Cell genomics·2026
Same author

Systematic evaluation of 24 extraction and library preparation combinations for metagenomic sequencing of SARS-CoV-2 in saliva.

bioRxiv : the preprint server for biology·2026
Same author

A Single-Cell and Spatial 3D Multi-omic Atlas of Developing Human Basal Ganglia and Inhibitory Neurons.

bioRxiv : the preprint server for biology·2026
Same author

Elastase-Treated Auricular Cartilage: Feasibility as a Substitute for Native Tarsus.

Ophthalmic plastic and reconstructive surgery·2026

Related Experiment Video

Updated: Jul 17, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.9K

Ensemble neural network model for detecting thyroid eye disease using external photographs.

Justin Karlin1, Lisa Gai2, Nathan LaPierre2

  • 1Division of Orbital and Ophthalmic Plastic Surgery, Stein and Doheny Eye Institutes, University of California, Los Angeles, CA, USA jkarlin@mednet.ucla.edu.

The British Journal of Ophthalmology
|September 20, 2022
PubMed
Summary

An artificial intelligence platform using deep learning accurately detects thyroid eye disease (TED). This AI tool shows promise in improving diagnostic accuracy and accessibility for specialist evaluation of TED.

Keywords:
Diagnostic tests/InvestigationImagingOrbitTelemedicine

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.9K
Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
05:41

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Published on: February 9, 2024

718

Related Experiment Videos

Last Updated: Jul 17, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.9K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.9K
Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
05:41

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Published on: February 9, 2024

718

Area of Science:

  • Ophthalmology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Thyroid eye disease (TED) diagnosis can be challenging.
  • Objective assessment of TED is crucial for timely intervention.
  • AI offers potential for enhanced diagnostic capabilities.

Purpose of the Study:

  • To develop and evaluate a deep learning platform for detecting thyroid eye disease (TED).
  • To compare the AI model's performance against ophthalmologists in identifying TED.

Main Methods:

  • A deep learning model was trained using 1944 clinical photographs.
  • Performance was evaluated on independent test sets (344 and 222 images).
  • Model performance was compared to 27 ophthalmologists using a subset of 50 images.

Main Results:

  • The AI model achieved high accuracy (89.2%), recall (93.4%), and F1 score (86.0%) on the test set.
  • Heatmaps confirmed the model identified key clinical features of TED.
  • The AI model outperformed the average ophthalmologist performance in detecting TED.

Conclusions:

  • A deep learning classifier represents a novel approach for identifying TED.
  • This AI platform is a significant first step toward improving diagnostic accuracy.
  • The tool has the potential to lower barriers to specialist evaluation for TED.