Applications and perspectives of artificial intelligence, machine learning and “dentronics” in dentistry: A literature review

Abstract

A BSTRACT Objective: The aim of this study was to describe artificial intelligence, machine learning, and “Dentronics” applications and perspectives in dentistry. Materials and Methods: A literature review was carried out to identify the applications of artificial intelligence in the field of dentistry. A specialized search for information was carried out in three databases such as Scopus, PubMed, and Web of Science. Manuscripts published from January 1988 to November 2021 were analyzed. Articles were included without any restriction by language or country. Results: Scopus, PubMed, and Web of Science were found to have 215, 1023, and 98 registered manuscripts, respectively. Duplicates (191 manuscripts) were eliminated. Finally, 4 letters, 12 editorials, 5 books, 1 erratum, 54 conference papers, 3 conference reviews, and 222 reviews were excluded. Conclusions: Artificial intelligence has revolutionized prediction, diagnosis, and therapeutic management in modern dentistry. Finally, artificial intelligence is a potential complement to managing future data in this area.

Modular training model for education of students in restorative and prosthodontic dentistry

“…Designing high‐quality models of such kind is always very time consuming and requires advanced designing, printing and postprocessing skills. It is certain that there will be tremendous improvements with the integration of Artificial Intelligence (AI) into designing software in the not so far future 29 …”

“…It is certain that there will be tremendous improvements with the integration of Artificial Intelligence (AI) into designing software in the not so far future. 29…”

Applications of artificial intelligence in the utilisation of imaging modalities in dentistry: A systematic review and meta-analysis of in-vitro studies

“…The Google Net Inception-v3 architecture, introduced in 2014, garnered acclaim for its exceptional performance across imaging-related applications. Trained on a comprehensive ImageNet dataset encompassing over a million images across 1000 object categories, this architecture's original design incorporates 22 deep layers, enabling the extraction of diverse scale features by applying convolutional filters of varying dimensions within the same layers [ [21] , [22] , [23] , [24] ].…”

“…AI can analyze large volumes of data and identify patterns that may be missed by human observers-therefore, in imaging diagnostics, as far as the literature is concerned in this regard, AI can offer precision and speed that significantly surpass traditional methods [ [11] , [12] , [13] ]. Similarly, AI can be used to predict disease progression based on patient data, enabling more personalized and effective treatment plans [ [21] , [22] , [23] , [24] ]. In dentistry and surgical fields, AI can assist in treatment planning, such as the design of orthodontic treatments or surgical interventions, by creating accurate 3D models and simulating outcomes.…”

“…In dentistry and surgical fields, AI can assist in treatment planning, such as the design of orthodontic treatments or surgical interventions, by creating accurate 3D models and simulating outcomes. This could lead to more precise, patient-specific treatments and potentially better outcomes [ [21] , [22] , [23] , [24] ]. Fig.…”