Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
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ISSN 1899–5276 (print)
ISSN 2451-2680 (online)
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Advances in Clinical and Experimental Medicine

2020, vol. 29, nr 3, March, p. 375–384

doi: 10.17219/acem/115083

Publication type: review article

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

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The ways of using machine learning in dentistry

Monika Elżbieta Machoy1,A,B,C,D,E,F, Liliana Szyszka-Sommerfeld1,B,F, Andras Vegh2,E,F, Tomasz Gedrange3,4,E,F, Krzysztof Woźniak1,E,F

1 Department of Orthodontics, Pomeranian Medical University, Szczecin, Poland

2 Department of Orofacial Orthopaedics and Orthodontics, Heim Pal Children’s Hospital, Budapest, Hungary

3 Division of Orthodontics, Technische Universität Dresden, Germany

4 Department of Oral Surgery, Wroclaw Medical University, Poland


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.

Key words

dentistry, clinical decision support systems, machine learning, artificial intelligence, CDSS

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