Machine (Deep) learning and finite element modeling

Yan Ting Lee, Tai Hsien Wu, Mei Ling Lin, Ching Chang Ko

Producción científica: Chapter


Finite element analysis (FEA) has been widely used to predict the biomechanical performance of various dental applications such as orthodontic tooth movement, implant components, and peri-implant bone. We begin with a brief introduction of the traditional FEA process and disadvantages of using FEA in clinical applications. Then, we review existing studies in which researchers use machine learning (ML) to address these disadvantages. Finally, we conclude that the combination of the FEA and ML is the best solution given that ML can facilitate the FEA computation, and FEA results can also enhance the accuracy of ML prediction.

Idioma originalEnglish (US)
Título de la publicación alojadaMachine Learning in Dentistry
EditorialSpringer International Publishing
Número de páginas6
ISBN (versión digital)9783030718817
ISBN (versión impresa)9783030718800
EstadoPublished - jul 24 2021

ASJC Scopus subject areas

  • General Dentistry
  • General Computer Science


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