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

Mechanical Efficiency of Real Machines01:14

Mechanical Efficiency of Real Machines

The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
However, in reality, no machine can be truly ideal, and all of them experience some...
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's proficiency in drug...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...

You might also read

Related Articles

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

Sort by
Same author

Aesthetic Component of the Index of Orthodontic Treatment Need (IOTN): Can large language models match the performance of orthodontists?

Korean journal of orthodontics·2026
Same author

Mechanical Performance of a Monolithic 3D-Printed Orthodontic Bracket-Crown System: An In-Vitro Study.

Materials (Basel, Switzerland)·2026
Same author

3D Gaussian Splatting vs. 2D Photogrammetry and Direct Anthropometry for Facial Measurements.

Orthodontics & craniofacial research·2026
Same author

Three-Dimensional Accuracy of Digitally Planned Orthodontic Tooth Movement in a Fully Customized Self-Ligating Lingual System.

Bioengineering (Basel, Switzerland)·2026
Same author

Camera-Based Monocular Depth Estimation in Orthodontics: Vision Transformer vs. CNN Model Performance.

Sensors (Basel, Switzerland)·2025
Same author

Accuracy of 3D Printer Technologies Using Digital Dental Models.

Turkish journal of orthodontics·2025

Related Experiment Video

Updated: Jun 29, 2026

Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment
07:32

Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment

Published on: February 23, 2024

1.8K

Orthodontic Biomechanical Reasoning with Multimodal Language Models: Performance and Clinical Utility.

Arda Arısan1, Celal Genç2, Gökhan Serhat Duran2

  • 1Independent Researcher, Ankara 06510, Turkey.

Bioengineering (Basel, Switzerland)
|November 27, 2025
PubMed
Summary

Multimodal large language models (LLMs) show potential for orthodontic biomechanical analysis. GPT-o3 demonstrated the highest performance in assessing orthodontic force systems, suggesting future clinical decision support capabilities.

Keywords:
AI in dental engineeringbiomechanical reasoningclinical decision supportmultimodal large language modelsorthodontic biomechanicsorthodontics

More Related Videos

Author Spotlight: Insights into an Efficient Murine Maxillary Orthodontic Model Protocol
04:11

Author Spotlight: Insights into an Efficient Murine Maxillary Orthodontic Model Protocol

Published on: October 27, 2023

1.3K
Studying Orthodontic Tooth Movement in Mice
07:17

Studying Orthodontic Tooth Movement in Mice

Published on: August 2, 2024

1.4K

Related Experiment Videos

Last Updated: Jun 29, 2026

Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment
07:32

Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment

Published on: February 23, 2024

1.8K
Author Spotlight: Insights into an Efficient Murine Maxillary Orthodontic Model Protocol
04:11

Author Spotlight: Insights into an Efficient Murine Maxillary Orthodontic Model Protocol

Published on: October 27, 2023

1.3K
Studying Orthodontic Tooth Movement in Mice
07:17

Studying Orthodontic Tooth Movement in Mice

Published on: August 2, 2024

1.4K

Area of Science:

  • Artificial Intelligence in Dentistry
  • Orthodontic Biomechanics
  • Clinical Decision Support Systems

Background:

  • Multimodal large language models (LLMs) are emerging as clinical support tools.
  • Their capability for orthodontic biomechanical reasoning remains unevaluated.
  • This study assesses LLMs' ability to analyze orthodontic treatment mechanics.

Purpose of the Study:

  • To systematically evaluate the capacity of multimodal large language models (LLMs) for orthodontic biomechanical reasoning.
  • To explore the potential role of LLMs in supporting orthodontic decision-making.
  • To compare the performance of different LLMs in analyzing orthodontic force systems.

Main Methods:

  • Five multimodal large language models (LLMs) analyzed 56 standardized intraoral photographs of orthodontic force systems.
  • Three experienced orthodontists evaluated model outputs on observation, interpretation, biomechanics, and confidence using a 5-point scale.
  • Inter-rater reliability and statistical comparisons between models were performed.

Main Results:

  • GPT-o3 achieved the highest composite score (66.8%), significantly outperforming Claude (57.8%), Gemini (52.6%), GPT-4.0 (48.8%), and Grok (38.8%).
  • Excellent inter-rater reliability was observed among expert evaluators (ICC: 0.786-0.802).
  • Model self-reported confidence poorly correlated with expert-rated output quality.

Conclusions:

  • Multimodal large language models (LLMs) demonstrate emerging potential in assisting orthodontic biomechanical assessment.
  • Expert-guided validation can enhance LLM contributions to clinical decision support in orthodontics.
  • LLMs may offer valuable support across various biomechanical scenarios in routine orthodontic care.