Related Experiment Video
Updated: Jun 19, 2026
05:49
Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Published on: February 23, 2024
Application of machine learning for data analysis in paediatric dentistry: a systematic review
I Gómez-Ríos1, V Saura-López1, A Pérez-Silva1
1Universidad de Murcia.
European Journal of Paediatric Dentistry
|May 28, 2025
Summary
Machine learning (ML) improves the analysis of pediatric oral diseases by identifying patterns in large datasets. This approach enhances early detection and cost-saving interventions for dental caries in children.
Area of Science:
- Oral Health
- Data Science
- Pediatric Dentistry
Background:
- Dental caries impacts millions of children globally.
- Machine learning (ML) and artificial intelligence (AI) offer advanced data analysis capabilities in dentistry.
- Existing research explores oral health's impact on quality of life and caries predictors.
Conclusions:
- Machine learning enhances the approach to pediatric oral diseases by analyzing complex data.
- Integration of ML into research and education is recommended for improved scientific evidence.
- Development of specific methodological guidelines and quality scales for ML studies in dentistry is crucial.
