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Related Concept Videos

Tooth Anatomy01:21

Tooth Anatomy

461
The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
The visible part of the tooth is referred to as the crown. It's covered by enamel, the hardest substance in the human body. The crown is uniquely shaped for each type of tooth, allowing for different functions such as cutting, tearing, or...
461

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Intraoperative Identification of Vital Radicular Pulp in a Tooth Diagnosed with Pulp Necrosis: Four-Year Outcome of Tampon Pulpotomy.

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Publishing Science That Matters: Iranian Endodontic Journal's New Era of Leadership in Endodontology.

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Surgical Management of a Large Radicular Cyst in a Maxillary Incisor Following Failed Regenerative Endodontics and Apical Plug in an Adolescent: A Case Report.

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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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Artificial Intelligence in Endodontics: A Scoping Review.

Saeed Asgary1

  • 1Iranian Center for Endodontic Research, Research Institute for Dental Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Iranian Endodontic Journal
|April 5, 2024
PubMed
Summary

Artificial intelligence (AI) enhances endodontic diagnostics and treatment planning. AI models, particularly neural networks, improve root canal analysis, lesion detection, and working-length determination for better clinical outcomes.

Keywords:
Artificial IntelligenceArtificial Neural NetworksConvolutional Neural NetworksDeep LearningDiagnostic PrecisionEndodontics

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Area of Science:

  • Dentistry
  • Endodontics
  • Artificial Intelligence

Background:

  • Endodontics is rapidly evolving with technological advancements.
  • Artificial intelligence (AI) offers transformative potential in dental diagnostics and treatment.

Purpose of the Study:

  • To review recent advancements in AI applications within endodontics.
  • To focus on the role of convolutional neural networks and artificial neural networks.

Main Methods:

  • Review of current literature on AI in endodontics.
  • Analysis of AI applications in image analysis and treatment prediction.
  • Examination of AI's role in cone-beam computed tomography (CBCT) interpretation.

Main Results:

  • AI models excel in root canal anatomy analysis, early periapical lesion detection, and working-length determination.
  • AI aids in predicting treatment success and identifying conditions like caries, pulpal inflammation, and fractures.
  • AI demonstrates high precision in recognizing landmarks and lesions on CBCT scans.

Conclusions:

  • AI significantly enhances accuracy and efficiency in endodontic procedures.
  • Further validation of AI reliability and practicality is crucial for clinical integration.
  • Ethical considerations regarding patient data and bias must be addressed for responsible AI implementation.