Browsing by Author "Albright, David"

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    A Novel Machine Learning Model for Predicting Orthodontic Treatment Duration
    (MDPI, 2023-08-23) Volovic, James; Badirl, Sarkhan; Ahmad, Sunna; Leavit, Landon; Mason, Taylor; Bhamidipalli, Surya Sruthi; Eckert, George; Albright, David; Turkkahraman, Hakan; Orthodontics and Oral Facial Genetics, School of Dentistry
    In the field of orthodontics, providing patients with accurate treatment time estimates is of utmost importance. As orthodontic practices continue to evolve and embrace new advancements, incorporating machine learning (ML) methods becomes increasingly valuable in improving orthodontic diagnosis and treatment planning. This study aimed to develop a novel ML model capable of predicting the orthodontic treatment duration based on essential pre-treatment variables. Patients who completed comprehensive orthodontic treatment at the Indiana University School of Dentistry were included in this retrospective study. Fifty-seven pre-treatment variables were collected and used to train and test nine different ML models. The performance of each model was assessed using descriptive statistics, intraclass correlation coefficients, and one-way analysis of variance tests. Random Forest, Lasso, and Elastic Net were found to be the most accurate, with a mean absolute error of 7.27 months in predicting treatment duration. Extraction decision, COVID, intermaxillary relationship, lower incisor position, and additional appliances were identified as important predictors of treatment duration. Overall, this study demonstrates the potential of ML in predicting orthodontic treatment duration using pre-treatment variables.
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    Dental Professionals’ Perspective on Direct-To-Consumer Clear Aligners
    (2021-07-01) Stewart, Kelton; Hoagburg, Brian; Keith, Caleb; Janik, Robert; Albright, David
    Background: Technology continues to drastically change the practice of orthodontics. One recent change includes direct-to-consumer (DTC) clear aligners, a model that omits a clinical exam by a licensed dentist and radiographic evaluation prior to initiating treatment. The purpose of this study was to collect quantitative data about dental professionals’ perspectives of the DTC treatment model. Materials and Methods: The Qualtrics-based survey was disseminated to dental professionals using several email lists. The survey included 26 questions, containing four domains: basic demographic information, perceptions of the direct-to-consumer clear aligner model, standards of orthodontic care, and patient experiences. Responses were summarized with descriptive statistics. Associations between respondent demographics and their perceptions about DTC clear aligner treatment and standards of orthodontic care were evaluated using Mantel- Haenszel Chi-squared tests. Results: There were 334 completed surveys, with 155 orthodontists (46.4%), 154 general dentists (46.1%), and 25 other dental specialties (7.5%) participants. More than 95% of respondents had a generally negative view of the DTC treatment model, with most respondents citing “suboptimal orthodontic care” and “misleading the public about orthodontic treatment” as the biggest influence in their view. Over 94% of respondents agreed that it is not within the standard of care to initiate orthodontic treatment without an in-person clinical exam or radiographs. Conclusion: Results suggest that dental professionals regard treatment rendered by DTC modalities not in the best interest of the public. Practical Implications: Dentists should be more active with educating patients about the impact of different dental treatment modalities.