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Artificial Intelligence and Its Application in Endodontics: A Review.

Zeeshan Heera Ahmed¹, Abdullah Muharib Almuharib², Abdulrahman Abdullah Abdulkarim²

¹Department of Restorative Dental Sciences and Endodontics, College of Dentistry, King Saud University, Riyadh, Saudi Arabia, Phone: +966502318766,

The Journal of Contemporary Dental Practice

|January 18, 2024

Summary

Artificial intelligence (AI) shows significant promise in endodontics, accurately aiding in diagnosis and treatment planning. Further research with larger datasets will enhance AI

Keywords:

Advantages and disadvantages of AI in endodontics Future of AI in endodontics.Artificial intelligence Comprehensive review Endodontics

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Area of Science:

Endodontics
Dental Artificial Intelligence
Diagnostic Technology

Background:

Artificial intelligence (AI) is increasingly integrated into dentistry, offering valuable tools across various specialties.
AI applications in dentistry include diagnosis of oral cancer, periodontal disease, dental caries, and treatment planning for orthognathic surgeries.
This review focuses on the application and performance of AI models specifically within endodontics.

Approach:

A comprehensive literature search was conducted using PubMed, Web of Science, and Google Scholar.
Keywords included "AI," "endodontics," and "dentistry" to identify relevant studies.
The review analyzed 56 papers detailing the use of AI in endodontic practice.

Key Points:

AI applications in endodontics encompass detecting periapical lesions, assessing root fractures, and determining working length.
AI models assist in predicting postoperative pain, analyzing root canal anatomy, and guiding retreatment decisions.
The accuracy of AI in these endodontic tasks can achieve up to 90%.

Conclusions:

AI demonstrates valuable applications and promising results in modern endodontics.
AI tools, combined with technologies like cone-beam computed tomography (CBCT), can significantly aid clinicians.
Larger, multicenter datasets are crucial for improving the external validity and reliability of AI models in endodontics.