ClinicalTrials.gov
public full text
Public Domain
Accuracy of Artificial Intelligence Technology in Detecting Number of Root Canals in Human Mandibular First Molars Obturated and Indicated for Retreatment: Diagnostic Accuracy Experimental Study
evaluate the accuracy of new AI technology for detecting root canals in mandibular first molars retreatment cases in comparison to dentist clinical access cavity and CBCT imaging.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Dental images processed with artificial intelligence — Richard Ricci (US10937160B1)#607067
- A novel AI-driven tool for automated root canal segmentation of single and bi-rooted teeth on cone-beam computed tomography#341015
- Diagnostic Accuracy of a Deep Learning Framework for Automated Evaluation of Root Canal Obturation Quality From Periapical Radiographs#908927
- <b>Beyond Diagnostic Accuracy: Calibration and Predictive Uncertainty of Artificial Intelligence Models for Oral and Dental Disease Diagnosis</b>#1097473
- Knowledge and Awareness of Performance Metrics in Dental Image Analysis With Artificial Intelligence: A Cross-Sectional Survey of Researchers and Clinicians.#170596
Record · ID 1033005
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive