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Artificial Intelligence–Based Multi-Stage System for Automated Angle’s Classification of Malocclusion from Intraoral Images in Orthodontics | Synapse
March 3, 2026
Artificial Intelligence–Based Multi-Stage System for Automated Angle’s Classification of Malocclusion from Intraoral Images in Orthodontics
SK
Shahab Kavousinejad
Research Institute for Endocrine Sciences
SG
Sara Ghazanfari
SM
Sara Alsadat Hosseinikhah Manshadi
Shahid Beheshti University of Medical Sciences
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Puntos clave
Automated classification of malocclusion could enhance orthodontic diagnostics, improving treatment planning.
The system achieves high accuracy in identifying malocclusions from intraoral images, with a 95% classification rate.
Using an artificial intelligence framework, this approach incorporates multi-stage processing to improve accuracy.
Implementation of this automated system may significantly reduce the time taken for orthodontic assessments.
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Kavousinejad et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75cadc6e9836116a25c02
https://doi.org/https://doi.org/10.1007/s10278-025-01826-7
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