Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Teeth

Teeth

The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin and...

Tooth Anatomy

Tooth Anatomy

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 grinding food.

You might also read

Related Articles

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

Sort by

Same author

Artificial Intelligence-Assisted Detection of the Elongated Styloid Process on Dental Radiographic Images: A Systematic Review and Literature Update.

Journal of clinical medicine·2026

Same author

Evidence of musculoskeletal pain sensitization in patients with multiple sclerosis: Case-control study.

Multiple sclerosis and related disorders·2026

Same author

Psychometrics properties of self-reported pain sensitivity measures in individuals with shoulder pain.

Journal of back and musculoskeletal rehabilitation·2026

Same author

Gingerol Enhances Osteogenic/Odontogenic Differentiation of Dental Pulp Stem Cells Impaired by Oxidative Stress via the Wnt/β-Catenin Pathway.

Journal of functional biomaterials·2026

Same author

CSF Levels of Baseline VCAM-1 and ICAM-1 Are Associated with Tau Pathology in Patients Demonstrating Cognitive Impairment.

Neurology international·2026

Same author

Occupational Dental Noise and Early Cochlear Changes: Evidence from Distortion Product Oto-Acoustic Emissions in Young Dentists.

Healthcare (Basel, Switzerland)·2026

Search research articles

Related Experiment Video

Updated: Jul 19, 2026

Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla

Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla

Published on: October 18, 2021

Artificial intelligence performance in maxillary canine impaction: a systematic review.

Hassan Ahmed Assiri^1,2, Budur Khalid Alsaanah³, Bushra Alshahrani³

¹Department of Diagnostic Sciences and Oral Biology and Periodontology, College of Dentistry, King Khalid University, Abha, Saudi Arabia. halmuawad@kku.edu.sa.

European Journal of Medical Research

|January 16, 2026

Summary

Artificial intelligence (AI) shows high accuracy in diagnosing impacted maxillary canines (MCI) and predicting eruption outcomes. AI tools can significantly aid clinicians in MCI diagnosis and treatment planning.

Keywords:

Artificial intelligence Cuspid Maxillary canine Tooth impaction

More Related Videos

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

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

Published on: February 23, 2024

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

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

Published on: February 23, 2024

Related Experiment Videos

Last Updated: Jul 19, 2026

Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla

Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla

Published on: October 18, 2021

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

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

Published on: February 23, 2024

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

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

Published on: February 23, 2024

Area of Science:

Dentistry
Medical Imaging
Artificial Intelligence

Background:

Maxillary canine impaction (MCI) is a common dental anomaly.
Accurate diagnosis and prediction are crucial for effective treatment planning.

Purpose of the Study:

To systematically review the literature on the utility and application of artificial intelligence (AI) in diagnosing and predicting maxillary canine impaction (MCI).

Main Methods:

A systematic search of four databases (PubMed, Scopus, Web of Science, Google Scholar) was conducted.
Included studies focused on AI applications in MCI diagnosis and prediction.
Diagnostic accuracy studies were assessed using QUADAS-2, and predictive studies using PROBASST.

Main Results:

Seven studies met the inclusion criteria, with a low risk of bias.
AI demonstrated high diagnostic accuracy (up to 98.3%) and efficient segmentation (Dice coefficient 0.99).
AI showed moderate-to-high predictive performance for 3D reconstruction and root resorption classification.

Conclusions:

AI exhibits high accuracy in localizing impacted maxillary canines and predicting eruption outcomes.
AI holds significant potential to support clinicians in MCI diagnosis, treatment planning, and management.
Further research with standardized methodologies and larger samples is needed to confirm clinical applicability.