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Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment

This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of curr...

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Autores principales: Strunga, Martin, Urban, Renáta, Surovková, Jana, Thurzo, Andrej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000479/
https://www.ncbi.nlm.nih.gov/pubmed/36900687
http://dx.doi.org/10.3390/healthcare11050683
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author Strunga, Martin
Urban, Renáta
Surovková, Jana
Thurzo, Andrej
author_facet Strunga, Martin
Urban, Renáta
Surovková, Jana
Thurzo, Andrej
author_sort Strunga, Martin
collection PubMed
description This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of current AI-based systems compared to conventional methods in diagnosing, assessing the progress of patients’ treatment and follow-up stability. The researchers used various online databases and identified diagnostic software and dental monitoring software as the most studied software in contemporary orthodontics. The former can accurately identify anatomical landmarks used for cephalometric analysis, while the latter enables orthodontists to thoroughly monitor each patient, determine specific desired outcomes, track progress, and warn of potential changes in pre-existing pathology. However, there is limited evidence to assess the stability of treatment outcomes and relapse detection. The study concludes that AI is an effective tool for managing orthodontic treatment from diagnosis to retention, benefiting both patients and clinicians. Patients find the software easy to use and feel better cared for, while clinicians can make diagnoses more easily and assess compliance and damage to braces or aligners more quickly and frequently.
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spelling pubmed-100004792023-03-11 Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment Strunga, Martin Urban, Renáta Surovková, Jana Thurzo, Andrej Healthcare (Basel) Review This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of current AI-based systems compared to conventional methods in diagnosing, assessing the progress of patients’ treatment and follow-up stability. The researchers used various online databases and identified diagnostic software and dental monitoring software as the most studied software in contemporary orthodontics. The former can accurately identify anatomical landmarks used for cephalometric analysis, while the latter enables orthodontists to thoroughly monitor each patient, determine specific desired outcomes, track progress, and warn of potential changes in pre-existing pathology. However, there is limited evidence to assess the stability of treatment outcomes and relapse detection. The study concludes that AI is an effective tool for managing orthodontic treatment from diagnosis to retention, benefiting both patients and clinicians. Patients find the software easy to use and feel better cared for, while clinicians can make diagnoses more easily and assess compliance and damage to braces or aligners more quickly and frequently. MDPI 2023-02-25 /pmc/articles/PMC10000479/ /pubmed/36900687 http://dx.doi.org/10.3390/healthcare11050683 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Strunga, Martin
Urban, Renáta
Surovková, Jana
Thurzo, Andrej
Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment
title Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment
title_full Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment
title_fullStr Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment
title_full_unstemmed Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment
title_short Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment
title_sort artificial intelligence systems assisting in the assessment of the course and retention of orthodontic treatment
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000479/
https://www.ncbi.nlm.nih.gov/pubmed/36900687
http://dx.doi.org/10.3390/healthcare11050683
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