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Summary

An AI system can now detect dental cavities from photos, improving access to care for millions facing barriers. This artificial intelligence tool visually explains its diagnoses, mimicking a dentist's approach.

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Area of Science:

Artificial Intelligence in Dentistry
Digital Health
Oral Health Diagnostics

Background:

Dental caries impact over 3.9 billion individuals globally.
Barriers like dentophobia, limited dentist availability, and lack of insurance hinder access to professional dental care.
Accurate diagnosis of dental cavities typically requires a trained dental professional.

Purpose of the Study:

To develop and evaluate an Artificial Intelligence (AI) system for detecting dental cavities in photographs.
To enhance the AI system's capability to analyze multiple teeth and four tooth surfaces, unlike previous single-tooth systems.
To incorporate visual explanation capabilities into the AI system for improved user understanding.

Main Methods:

Collected and de-identified 506 images from online sources and human participants.
Utilized a ResNet-27 architecture with curriculum learning for optimal model performance.
Implemented Local Interpretable Model Agnostic Explanation (LIME) for generating visual diagnostic rationales.

Main Results:

The AI system achieved 82.8% accuracy and 1.0 sensitivity in detecting cavities.
The developed system can analyze photographs containing multiple teeth and four tooth surfaces.
Visual explanations were successfully generated, enhancing the AI's diagnostic transparency.

Conclusions:

The AI system demonstrates significant potential for accurate dental cavity detection from photographs.
The system's ability to analyze multiple teeth and provide visual explanations addresses key limitations of previous technologies.
This AI tool offers a promising solution to improve dental care accessibility and diagnostic support.