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Applied artificial intelligence in dentistry: emerging data modalities and modeling approaches.

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Artificial intelligence (AI), particularly machine learning (ML), is revolutionizing dental medicine. AI enhances diagnostics, risk prediction, and clinical decision-making, improving oral health outcomes and research efficiency.

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Area of Science:

  • Dental Medicine
  • Artificial Intelligence
  • Machine Learning

Background:

  • Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into medical disciplines, including dentistry.
  • ML identifies patterns in data, mirroring human learning processes.
  • Current clinical dentistry utilizes ML for diagnostics, risk stratification, and decision support to enhance care.

Purpose of the Study:

  • To provide a comprehensive overview of AI applications in dental medicine from an ML perspective.
  • To explore AI's role in diagnostic, prognostic, and generative tasks within dentistry.
  • To present data modalities in dentistry and their compatibility with AI methods.

Main Methods:

  • Review of current literature on AI and ML in dental medicine.
  • Analysis of AI applications across diagnostic, prognostic, and generative tasks.
  • Examination of data modalities and their suitability for AI integration.

Main Results:

  • AI, especially ML, is significantly advancing dental diagnostics, risk prediction, and clinical decision support.
  • ML is widely adopted in dental research, from basic science to clinical investigations.
  • Various data modalities in dentistry are compatible with different AI techniques.

Conclusions:

  • AI offers substantial potential to improve oral health care efficiency, outcomes, and reduce disparities.
  • Challenges and limitations in AI implementation in dentistry exist but are being addressed.
  • Future possibilities for AI in dental medicine are extensive, requiring careful consideration.