Literature DB >> 33340123

Promises and perils of artificial intelligence in dentistry.

F Pethani1.   

Abstract

Artificial intelligence (AI) is a subdiscipline of computer science that has made substantial progress in medicine and there is a growing body of AI research in dentistry. Dentists should have an understanding of the foundational concepts and the ability to critically evaluate dental research in AI. Machine learning (ML) is a subfield of AI that most dental AI research is dedicated to. The most prolific area of ML research is automated interpretation of dental imaging. Other areas include providing treatment recommendations, predicting future disease and treatment outcomes. The research impact is limited by small datasets that do not harness the positive correlation between very large datasets and ML performance. There is also a need to standardize research methodologies and utilize performance metrics that are appropriate for the clinical context. In addition to research challenges, this article discusses the ethical, legal and logistical considerations associated with implementation in clinical practice. This includes explainable AI, model bias, data privacy and security. The future implications of AI in dentistry involve a promise for a novel form of practicing dentistry however, the effect of AI on patient outcomes is yet to be determined.
© 2020 Australian Dental Association.

Entities:  

Keywords:  artificial intelligence; dentistry; imaging; machine learning; neural networks

Year:  2021        PMID: 33340123     DOI: 10.1111/adj.12812

Source DB:  PubMed          Journal:  Aust Dent J        ISSN: 0045-0421            Impact factor:   2.291


  5 in total

Review 1.  Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls.

Authors:  Shankargouda Patil; Sarah Albogami; Jagadish Hosmani; Sheetal Mujoo; Mona Awad Kamil; Manawar Ahmad Mansour; Hina Naim Abdul; Shilpa Bhandi; Shiek S S J Ahmed
Journal:  Diagnostics (Basel)       Date:  2022-04-19

2.  Artificial Intelligence: A New Diagnostic Software in Dentistry: A Preliminary Performance Diagnostic Study.

Authors:  Francesca De Angelis; Nicola Pranno; Alessio Franchina; Stefano Di Carlo; Edoardo Brauner; Agnese Ferri; Gerardo Pellegrino; Emma Grecchi; Funda Goker; Luigi Vito Stefanelli
Journal:  Int J Environ Res Public Health       Date:  2022-02-02       Impact factor: 3.390

Review 3.  Scope and challenges of machine learning-based diagnosis and prognosis in clinical dentistry: A literature review.

Authors:  Lilian Toledo Reyes; Jessica Klöckner Knorst; Fernanda Ruffo Ortiz; Thiago Machado Ardenghi
Journal:  J Clin Transl Res       Date:  2021-07-30

Review 4.  Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis.

Authors:  Andrej Thurzo; Wanda Urbanová; Bohuslav Novák; Ladislav Czako; Tomáš Siebert; Peter Stano; Simona Mareková; Georgia Fountoulaki; Helena Kosnáčová; Ivan Varga
Journal:  Healthcare (Basel)       Date:  2022-07-08

5.  Diagnosis of Tooth Prognosis Using Artificial Intelligence.

Authors:  Sang J Lee; Dahee Chung; Akiko Asano; Daisuke Sasaki; Masahiko Maeno; Yoshiki Ishida; Takuya Kobayashi; Yukinori Kuwajima; John D Da Silva; Shigemi Nagai
Journal:  Diagnostics (Basel)       Date:  2022-06-09
  5 in total

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