Browsing by Subject "Tooth Extraction"

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    A machine learning model for orthodontic extraction/non-extraction decision in a racially and ethnically diverse patient population
    (Elsevier, 2023-09) Mason, Taylor; Kelly, Kynnedy M.; Eckert, George; Dean, Jeffrey A.; Dundar, M. Murat; Turkkahraman, Hakan; Orthodontics and Oral Facial Genetics, School of Dentistry
    Introduction The purpose of the present study was to create a machine learning (ML) algorithm with the ability to predict the extraction/non-extraction decision in a racially and ethnically diverse sample. Methods Data was gathered from the records of 393 patients (200 non-extraction and 193 extraction) from a racially and ethnically diverse population. Four ML models (logistic regression [LR], random forest [RF], support vector machine [SVM], and neural network [NN]) were trained on a training set (70% of samples) and then tested on the remaining samples (30%). The accuracy and precision of the ML model predictions were calculated using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve. The proportion of correct extraction/non-extraction decisions was also calculated. Results The LR, SVM, and NN models performed best, with an AUC of the ROC of 91.0%, 92.5%, and 92.3%, respectively. The overall proportion of correct decisions was 82%, 76%, 83%, and 81% for the LR, RF, SVM, and NN models, respectively. The features found to be most helpful to the ML algorithms in making their decisions were maxillary crowding/spacing, L1-NB (mm), U1-NA (mm), PFH:AFH, and SN-MP(̊), although many other features contributed significantly. Conclusions ML models can predict the extraction decision in a racially and ethnically diverse patient population with a high degree of accuracy and precision. Crowding, sagittal, and vertical characteristics all featured prominently in the hierarchy of components most influential to the ML decision-making process.
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    Prevalence of Temporomandibular Dysfunction in the Class II Division I Untreated Patient and the Class II Division I Orthodontically Treated Patient with Premolar Extractions
    (1990) Bolon, Rebecca Anne; Roberts, W. Eugene; Simmon, Kirt E.; Hohlt, William F.; Mora, Assad F.; Shanks, James C.; Garetto, Lawrence P.
    Orthodontics has been suggested as a form of treatment for temporomandibular (TM) disorders, while at the same time orthodontic treatment accompanied by premolar extraction has been blamed for producing iatrogenic internal derangement of the TM joint. Signs and symptoms of TM disorders were evaluated by a clinical history questionnaire and a thorough clinical examination. The clinical examination entailed TMJ manipulation, palpation of muscles and TM joints, and recording the active range of motion. The 45 patients in each pre-treatment and post-treatment group were obtained from the Orthodontic Clinic at the Indiana University School of Dentistry. With the exception of age, there was no statistically significant difference between the two groups.