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福利姬视频White Paper No. 1106, Dentistry - Overview of Artificial and Augmented Intelligence Uses in Dentistry

This document highlights the use of AI and Augmented Intelligence across clinical areas in dentistry, including diagnostics, treatment, imaging, and teledentistry, as well as in non-clinical areas like claims processing, payment integrity, and regulatory considerations. It also addresses dental practice administration and relevant global and FDA regulatory frameworks.

福利姬视频Technical Report No. 1109, Dentistry – Image Analysis Systems Using Artificial Intelligence

This Augmented Intelligence (AI) for dental image analysis is progressing toward automated identification of common dental diseases and disorders. This technical report (TR) presents key principles of the Machine Learning (ML) at AI’s core, including its training and validation, and provides clinicians with standard methods for its evaluation, including considerations of its risks and benefits.

福利姬视频Standard No. 1110-1, Dentistry - Validation Dataset Guidance for Image Analysis Systems Using Artificial Intelligence, Part 1: Image Annotation and Data Collection

• Standards for Content: Establishment of qualitative, quantitative, and novelty measures of image samples needed for each intended use. Establishment of parameters for providing coverage of various subpopulations.  Establishment of needed metadata elements to support the AI system validation process, to support statistical and other analyses of the dataset itself, and to support security and ethics requirements.
• Standards for Collection: Establishment of credentials and processes for collecting image samples, and for tagging images with Dx or Tx findings, including the provenance of that tagging.  Establishment of requirements for obtaining and maintaining patient permission for including images in the Dataset.  Establishment of security requirements for images and metadata in the dataset.
• Standards for Calculation: Establishment of processes for AI System validation using the Validation Dataset, and for calculation of AI System performance based on that validation.
• Standards for Confidence: Establishment of levels of acceptability for methods of establishing ground truth of image samples.  Establishment of a process for sequestering the Validation Dataset from the development of the system to be validated. Establishment of requirements for public information about any Validation Dataset, such as a list of intended uses, statistics about the methods of determining ground truth, statistics about the number of patients and samples by subpopulation, statistics about the system performance, and a statement of sequestration.

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