Next Article in Journal
Mechatronics Design of a Clinostat Agriculture Space System for Biomimetic Phyto-Growth in Microgravity (Phyto-G) and 3D-Motion Computer Simulation on Hydroponic Environment
Next Article in Special Issue
SE-SNN: Squeeze-and-Excitation-Enhanced Spiking Neural Networks with Learnable Neuron Dynamics for Event-Based Vision
Previous Article in Journal
Comparative Study on the Surface Properties of Synthetic Carbonated Hydroxyapatite and Natural Hydroxyapatite Before and After Contact with Solutions with de- and Remineralization Activity
Previous Article in Special Issue
A Trustable Spine Abnormalities Classification System Using ResNet50 and VGG16 Supported by Explainable Artificial Intelligence
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Artificial Intelligence Applications in Pediatric Dentistry: A Comprehensive Review

1
Department of Pediatric Dentistry, Faculty of Dentistry, Gazi University, 06490 Ankara, Turkey
2
Department of Pediatric Dentistry, Faculty of Dentistry, Karabük University, 78050 Karabük, Turkey
*
Author to whom correspondence should be addressed.
Biomimetics 2026, 11(5), 339; https://doi.org/10.3390/biomimetics11050339
Submission received: 14 April 2026 / Revised: 6 May 2026 / Accepted: 11 May 2026 / Published: 14 May 2026
(This article belongs to the Special Issue Artificial Intelligence (AI) in Biomedical Engineering: 2nd Edition)

Abstract

The application of artificial intelligence (AI) technologies in pediatric dentistry has expanded rapidly and is assuming an increasingly important role in the assessment of oral health and diagnostic processes in children. In particular, image-based analyses and data-driven predictive models offer significant potential to enhance diagnostic accuracy and reduce observer-dependent variability. This review addresses AI applications in pediatric dentistry within a structured framework, summarizing the methodological foundations of machine learning and deep learning approaches while critically evaluating the current body of evidence. It further identifies key limitations in the existing literature and outlines future research priorities, aiming to provide a perspective for the safe and sustainable clinical integration of AI in pediatric dentistry.
Keywords: artificial intelligence; deep learning; machine learning; pediatric dentistry artificial intelligence; deep learning; machine learning; pediatric dentistry
Graphical Abstract

Share and Cite

MDPI and ACS Style

Hatipoğlu Palaz, Z.; Akın, Y.; Karademir, Ü.; Çege, E.E.; Bani, M. Artificial Intelligence Applications in Pediatric Dentistry: A Comprehensive Review. Biomimetics 2026, 11, 339. https://doi.org/10.3390/biomimetics11050339

AMA Style

Hatipoğlu Palaz Z, Akın Y, Karademir Ü, Çege EE, Bani M. Artificial Intelligence Applications in Pediatric Dentistry: A Comprehensive Review. Biomimetics. 2026; 11(5):339. https://doi.org/10.3390/biomimetics11050339

Chicago/Turabian Style

Hatipoğlu Palaz, Zeliha, Yasemin Akın, Ümmühan Karademir, Ecem Elif Çege, and Mehmet Bani. 2026. "Artificial Intelligence Applications in Pediatric Dentistry: A Comprehensive Review" Biomimetics 11, no. 5: 339. https://doi.org/10.3390/biomimetics11050339

APA Style

Hatipoğlu Palaz, Z., Akın, Y., Karademir, Ü., Çege, E. E., & Bani, M. (2026). Artificial Intelligence Applications in Pediatric Dentistry: A Comprehensive Review. Biomimetics, 11(5), 339. https://doi.org/10.3390/biomimetics11050339

Article Metrics

Back to TopTop