Literature DB >> 32207586

The ways of using machine learning in dentistry.

Monika Elżbieta Machoy1, Liliana Szyszka-Sommerfeld1, Andras Vegh2, Tomasz Gedrange3,4, Krzysztof Woźniak1.   

Abstract

Innovative computer techniques are starting to be employed not only in academic research, but also in commercial production, finding use in many areas of dentistry. This is conducive to the digitalization of dentistry and its increasing treatment and diagnostic demands. In many areas of dentistry, such as orthodontics and maxillofacial surgery, but also periodontics or prosthetics, only a correct diagnosis ensures the correct treatment plan, which is the only way to restore the patient's health. The diagnosis and treatment plan is based on the specialist's knowledge, but is subject to a large, multi-factorial risk of error. Therefore, the introduction of multiparametric pattern recognition methods (statistics, machine learning and artificial intelligence (AI)) is a great hope for both the physicians and the patients. However, the general use of clinical decision support systems (CDSS) in a dental clinic is not yet realistic and requires work in many aspects - methodical, technological and business. The article presents a review of the latest attempts to apply AI, such as CDSS or genetic algorithms (GAs) in research and clinical dentistry, taking under consideration all of the main dental specialties. Work on the introduction of public CDSS has been continued for years. The article presents the latest achievements in this field, analyzing their real-life application and credibility.

Entities:  

Keywords:  CDSS; artificial intelligence; clinical decision support systems; dentistry; machine learning

Year:  2020        PMID: 32207586     DOI: 10.17219/acem/115083

Source DB:  PubMed          Journal:  Adv Clin Exp Med        ISSN: 1899-5276            Impact factor:   1.727


  7 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.  Machine learning for identification of dental implant systems based on shape - A descriptive study.

Authors:  Veena Basappa Benakatti; Ramesh P Nayakar; Mallikarjun Anandhalli
Journal:  J Indian Prosthodont Soc       Date:  2021 Oct-Dec

3.  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 4.  Current state of dental informatics in the field of health information systems: a scoping review.

Authors:  Ballester Benoit; Bukiet Frédéric; Dufour Jean-Charles
Journal:  BMC Oral Health       Date:  2022-04-19       Impact factor: 3.747

Review 5.  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

6.  Diagnosis of temporomandibular disorders using artificial intelligence technologies: A systematic review and meta-analysis.

Authors:  Nayansi Jha; Kwang-Sig Lee; Yoon-Ji Kim
Journal:  PLoS One       Date:  2022-08-18       Impact factor: 3.752

7.  Analysis of the Impact of Oral Health on Adolescent Quality of Life Using Standard Statistical Methods and Artificial Intelligence Algorithms.

Authors:  Milica Gajic; Jovan Vojinovic; Katarina Kalevski; Maja Pavlovic; Veljko Kolak; Branislava Vukovic; Rasa Mladenovic; Ema Aleksic
Journal:  Children (Basel)       Date:  2021-12-08
  7 in total

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