Reliability and time-based efficiency of artificial intelligence-based automatic digital model analysis system.
Eur J Orthod
; 45(6): 712-721, 2023 11 30.
Article
em En
| MEDLINE
| ID: mdl-37418746
ABSTRACT
OBJECTIVES:
To compare the reliability, reproducibility, and time-based efficiency of automatic digital (AD) and manual digital (MD) model analyses using intraoral scan models. MATERIAL ANDMETHODS:
Two examiners analysed 26 intraoral scanner records using MD and AD methods for orthodontic modelling. Tooth size reproducibility was confirmed using a Bland-Altman plot. The Wilcoxon signed-rank test was conducted to compare the model analysis parameters (tooth size, sum of 12-teeth, Bolton analysis, arch width, arch perimeter, arch length discrepancy, and overjet/overbite) for each method, including the time taken for model analysis.RESULTS:
The MD group exhibited a relatively larger spread of 95% agreement limits when compared with AD group. The standard deviations of repeated tooth measurements were 0.15 mm (MD group) and 0.08 mm (AD group). The mean difference values of the 12-tooth (1.80-2.38 mm) and arch perimeter (1.42-3.23 mm) for AD group was significantly (P < 0.001) larger than that for the MD group. The arch width, Bolton, and overjet/overbite were clinically insignificant. The overall mean time required for the measurements was 8.62 min and 0.56 min for the MD and AD groups, respectively.LIMITATIONS:
Validation results may vary in different clinical cases because our evaluation was limited to mild-to-moderate crowding in the complete dentition.CONCLUSIONS:
Significant differences were observed between AD and MD groups. The AD method demonstrated reproducible analysis in a considerably reduced timeframe, along with a significant difference in measurements compared to the MD method. Therefore, AD analysis should not be interchanged with MD, and vice versa.
Texto completo:
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Sobremordida
/
Má Oclusão
Tipo de estudo:
Guideline
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article