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

Classification of Bones01:18

Classification of Bones

5.5K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
5.5K
Classification of Connective Tissues01:30

Classification of Connective Tissues

10.6K
The connective tissues have different properties and functions in the human body. They are broadly categorized into proper, supporting, or fluid connective tissues.
Connective Tissue Proper
Connective tissue proper is the most abundant class of connective tissues. As its name implies, it predominantly connects different tissues in the body. Depending on the cell types, ground substance, viscosity, and fiber types in the ECM, connective tissue proper is further categorized into loose and dense....
10.6K
Classification of Illness01:17

Classification of Illness

7.5K
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...
7.5K
Classification of Skeletal Muscle Relaxants01:28

Classification of Skeletal Muscle Relaxants

2.5K
Skeletal muscle relaxants are a group of drugs that can reduce muscle stiffness and induce temporary paralysis to relieve pain. These agents can act centrally to reduce muscle tone or spasms in painful conditions such as multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), or spinal injuries; they are called antispasmodics or spasmolytics.
Peripherally acting skeletal muscle relaxants interfere with the neurotransmission at the neuromuscular end plate to induce paralysis during...
2.5K
Tooth Anatomy01:21

Tooth Anatomy

473
The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
The visible part of the tooth is referred to as the crown. It's covered by enamel, the hardest substance in the human body. The crown is uniquely shaped for each type of tooth, allowing for different functions such as cutting, tearing, or...
473
Knee Joint01:23

Knee Joint

1.8K
The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...
1.8K

You might also read

Related Articles

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

Sort by
Same author

A Community-Based Usability Study of an AI-Enabled Oral Cancer Screening App Operated by Village Health Volunteers: Mixed Methods Study.

JMIR mHealth and uHealth·2026
Same author

Photorealistic synthesis of oral lichen planus and lichenoid lesions enhances deep-learning segmentation in intra-oral photographs.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same author

Deep learning-based object detection of restorative dental instruments with potential implications for workflow automation and infection control in dental supply units.

Scientific reports·2025
Same author

Salivary glucose, salivary interleukin-18, glycemic control, and periodontal status in patients with type 2 diabetes mellitus.

Scientific reports·2025
Same author

Virtual reality simulation for learning minimally invasive endodontics: a randomized controlled trial.

BMC medical education·2025
Same author

Performance of deep learning models for the classification and object detection of different oral white lesions using photographic images.

Scientific reports·2025
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

Related Experiment Video

Updated: Jul 5, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

849

Temporomandibular Joint Disorders Multi-Class Classification Using Deep Learning.

Bhornsawan Thanathornwong1, Treesukon Treebupachatsakul2, Thitirat Teechot2

  • 1Faculty of Dentistry, Srinakharinwirot University, Bangkok, Thailand.

Studies in Health Technology and Informatics
|January 25, 2024
PubMed
Summary
This summary is machine-generated.

Deep learning accurately classified temporomandibular joint (TMJ) disorders and normal variations in panoramic radiographs. DenseNet-121 achieved 99% accuracy, aiding in correct TMJ disorder diagnosis and treatment.

Keywords:
Temporomandibular joint disordersclassificationdeep learning

More Related Videos

Temporomandibular Joint Pain Measurement by Bite Force and Von Frey Filament Assays in Mice
06:37

Temporomandibular Joint Pain Measurement by Bite Force and Von Frey Filament Assays in Mice

Published on: September 13, 2024

933
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

2.5K

Related Experiment Videos

Last Updated: Jul 5, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

849
Temporomandibular Joint Pain Measurement by Bite Force and Von Frey Filament Assays in Mice
06:37

Temporomandibular Joint Pain Measurement by Bite Force and Von Frey Filament Assays in Mice

Published on: September 13, 2024

933
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

2.5K

Area of Science:

  • Dentistry
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Temporomandibular joint (TMJ) disorders are often misdiagnosed due to confusion with normal anatomical variations.
  • Misinterpretation of TMJ features can lead to ineffective treatment strategies and patient dissatisfaction.

Purpose of the Study:

  • To evaluate the efficacy of deep learning algorithms, specifically DenseNet-121 and InceptionV3, in classifying normal TMJ variations and disorders.
  • To assess the performance of these AI models using panoramic radiographs.

Main Methods:

  • A dataset of 1,710 panoramic radiographs was utilized for the study.
  • Two deep learning models, DenseNet-121 and InceptionV3, were employed for multi-class classification tasks.
  • Performance metrics including overall accuracy and Area Under the Curve (AUC) were calculated.

Main Results:

  • DenseNet-121 demonstrated an overall accuracy of 0.99 (99%).
  • InceptionV3 achieved an overall accuracy of 0.95 (95%).
  • Both models exhibited high performance with AUC values ranging from 0.99 to 1.00.

Conclusions:

  • Deep learning algorithms, particularly DenseNet-121, show exceptional capability in accurately classifying TMJ disorders and normal variations from panoramic radiographs.
  • These findings suggest a promising role for AI in improving the diagnostic accuracy of TMJ disorders, potentially reducing treatment failures.