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Artificial intelligence-designed single molar dental prostheses: A protocol of prospective experimental study.

Reinhard Chun Wang ChauMing ChongKhaing Myat ThuNate Sing Po ChuMohamad Koohi-MoghadamRichard Tai-Chiu HsungColman McGrathWalter Yu-Hang Lam
Published in: PloS one (2022)
This article describes the protocol of a prospective experimental study, which aims to train and to validate the AI system for design of single molar dental prostheses. Maxillary and mandibular dentate teeth models will be collected and digitized from at least 250 volunteers. The (original) digitized maxillary teeth models will be duplicated and processed by removal of right maxillary first molars (FDI tooth 16). Teeth models will be randomly divided into training and validation sets. At least 200 training sets of the original and the processed digitalized teeth models will be input into 3D Generative Adversarial Network (GAN) for training. Among the validation sets, tooth 16 will be generated by AI on 50 processed models and the morphology and 3D position of AI-generated tooth will be compared to that of the natural tooth in the original maxillary teeth model. The use of different GAN algorithms and the need of antagonist mandibular teeth model will be investigated. Results will be reported following the CONSORT-AI.
Keyphrases
  • cone beam computed tomography
  • artificial intelligence
  • machine learning
  • deep learning
  • big data
  • randomized controlled trial
  • oral health
  • mass spectrometry
  • high resolution