A review of deep learning in dentistry

Chenxi Huang, Jiaji Wang, Shuihua Wang, Yudong Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

Oral diseases have a significant impact on human health, often going unnoticed in their early stages. Deep learning, a promising field in artificial intelligence, has shown remarkable success in various domains, especially dentistry. This paper aims to provide an overview of recent research on deep learning applications in dentistry, with a focus on dental imaging. Deep learning algorithms perform well in difficult tasks such as image segmentation and recognition, enabling accurate identification of oral conditions and abnormalities. Integration of deep learning with other oral health data offers a holistic understanding of the relationship between oral and systemic health. However, there are still many challenges that need to be addressed.

Original languageEnglish
Article number126629
JournalNeurocomputing
Volume554
DOIs
Publication statusPublished - 14 Oct 2023
Externally publishedYes

Keywords

  • Deep learning
  • Image classification
  • Image segmentation
  • Oral diseases

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