Innovative CNN-Based System for Approximal Caries Diagnosis in Pediatric Patients: A Game-Changer in Pediatric Dentistry

Posted: January 6, 2025
This pilot study focused on utilizing convolutional neural networks for the accurate diagnosis of approximal caries in pediatric patients aged 5-12 years. By creating a unique dataset of digital periapical radiographic images and employing various augmentation methods, the developed detection system achieved high precision, accuracy, recall, and F1 value. The system demonstrated a promising potential for efficient identification of approximal caries in children, highlighting the significance of artificial intelligence in pediatric dentistry.

This article summary was generated by AI. To view the full article, click the link here: https://pubmed.ncbi.nlm.nih.gov/39761112/
Views: 2
Sponsors
Townie Perks
Townie® Poll
Who or what do you turn to for most financial advice regarding your practice?
  
The Dentaltown Team, Farran Media Support
Phone: +1-480-445-9710
Email: support@farranmedia.com
©2025 Dentaltown, a division of Farran Media • All Rights Reserved
9633 S. 48th Street Suite 200 • Phoenix, AZ 85044 • Phone:+1-480-598-0001 • Fax:+1-480-598-3450