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Malocclusion, Angle Class II

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Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age.

International journal of oral and maxillofacial surgery
This observational study aimed to use artificial intelligence to describe the impact of orthognathic treatment on facial attractiveness and age appearance. Pre- and post-treatment photographs (n=2164) of 146 consecutive orthognathic patients were col...

[Cranial Facial 3D Biometry: Statistical analysis of Class II disharmonies].

L' Orthodontie francaise
We could study Cone Beam documents of patients consulting in ORL with standard Angle Class I occlusion (45 ND), patients consulting in orthodontics with an orthodontic Class II (51 APNS) and patients with a surgical Class II (83 APS). The used 3D bio...

Facial profile evaluation and prediction of skeletal class II patients during camouflage extraction treatment: a pilot study.

Head & face medicine
BACKGROUND: The evaluation of the facial profile of skeletal Class II patients with camouflage treatment is of great importance for patients and orthodontists. The aim of this study is to explore the key factors in evaluating the facial profile esthe...

Artificial intelligence as a prediction tool for orthognathic surgery assessment.

Orthodontics & craniofacial research
INTRODUCTION: An ideal orthodontic treatment involves qualitative and quantitative measurements of dental and skeletal components to evaluate patients' discrepancies, such as facial, occlusal, and functional characteristics. Deciding between orthodon...

Lateral cephalometric parameters among Arab skeletal classes II and III patients and applying machine learning models.

Clinical oral investigations
BACKGROUND: The World Health Organization considers malocclusion one of the most essential oral health problems. This disease influences various aspects of patients' health and well-being. Therefore, making it easier and more accurate to understand a...

Three-dimensional analysis of mandibular and condylar growth using artificial intelligence tools: a comparison of twin-block and Frankel II Appliances.

BMC oral health
BACKGROUND: Analyzing the morphological growth changes upon mandibular advancement between Twin Block (TB) and Functional Regulator II (FR2) in Class II patients involves measuring the condylar and mandibular changes in terms of linear and volumetric...

Hierarchical clustering analysis & machine learning models for diagnosing skeletal classes I and II in German patients.

BMC oral health
BACKGROUND: Classification is one of the most common tasks in artificial intelligence (AI) driven fields in dentistry and orthodontics. The AI abilities can significantly improve the orthodontist's critical mission to diagnose and treat patients prec...