AIMC Topic: Orthodontics, Corrective

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Quantitative analysis and clinical determinants of orthodontically induced root resorption using automated tooth segmentation from CBCT imaging.

BMC oral health
BACKGROUND: Orthodontically induced root resorption (OIRR) is difficult to assess accurately using traditional 2D imaging due to distortion and low sensitivity. While CBCT offers more precise 3D evaluation, manual segmentation remains labor-intensive...

Predicting changes of incisor and facial profile following orthodontic treatment: a machine learning approach.

Head & face medicine
BACKGROUND: Facial aesthetics is one of major motivations for seeking orthodontic treatment. However, even for experienced professionals, the impact and extent of incisor and soft tissue changes remain largely empirical. With the application of inter...

Research of orthodontic soft tissue profile prediction based on conditional generative adversarial networks.

Journal of dentistry
OBJECTIVE: This study constructed a new conditional generative adversarial network (CGAN) model to predict changes in lateral appearance following orthodontic treatment.

Automatic 3-dimensional quantification of orthodontically induced root resorption in cone-beam computed tomography images based on deep learning.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: Orthodontically induced root resorption (OIRR) is a common and undesirable consequence of orthodontic treatment. Traditionally, studies employ manual methods to conduct 3-dimensional quantitative analysis of OIRR via cone-beam computed ...

Prediction of patient cooperation before orthodontic treatment: Handwriting and artificial intelligence.

Journal of the World federation of orthodontists
BACKGROUND: The purpose of this study was to compare the success of various convolutional neural network (CNN) models trained with handwriting samples in predicting patient cooperation.

Evaluation of different machine learning algorithms for extraction decision in orthodontic treatment.

Orthodontics & craniofacial research
INTRODUCTION: The extraction decision significantly affects the treatment process and outcome. Therefore, it is crucial to make this decision with a more objective and standardized method. The objectives of this study were (1) to identify the best-pe...

Clinical evaluation of Artificial Intelligence Driven Remote Monitoring technology for assessment of patient oral hygiene during orthodontic treatment.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: This study aimed to clinically evaluate the accuracy of Dental Monitoring's (DM) artificial intelligence (AI) image analysis and oral hygiene notification algorithm in identifying oral hygiene and mucogingival conditions.

Novel Machine Learning Algorithms for Prediction of Treatment Decisions in Adult Patients With Class III Malocclusion.

Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
BACKGROUND: Management of Class III (Cl III) dentoskeletal phenotype is often expert-driven.

Cleft Skeletal Asymmetry: Asymmetry Index, Classification and Application.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
OBJECTIVE: To quantitatively measure the extent of 3D asymmetry of the facial skeleton in patients with unilateral cleft lip and palate (UCLP) using an asymmetry index (AI) approach, and to illustrate the applicability of the index in guiding and mea...