Evaluating the Accuracy of Automated Orthodontic Digital Setup Models

Woo, Hyein; Jha, Nayansi; Kim, Inah; Sung, Si‐Young

doi:10.1053/j.sodo.2022.12.010

Cited by 9 publications

(6 citation statements)

References 16 publications

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“…Therefore, accurately predicting treatment outcomes is crucial for both practitioners and patients. Fortunately, a growing body of literature demonstrates the effectiveness of AI in predicting orthodontic and orthognathic treatment outcomes [155][156][157][158][159][160][161][162][163].…”

Section: Treatment Outcome Predictionmentioning

confidence: 99%

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning—A Comprehensive Review

Kazimierczak,

Serafin

et al. 2024

JCM

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The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. This review explores the principles of AI, its applications in orthodontics, and its implementation in clinical practice. A comprehensive literature review was conducted, focusing on AI applications in dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, decision making, and patient telemonitoring. Due to study heterogeneity, no meta-analysis was possible. AI has demonstrated high efficacy in all these areas, but variations in performance and the need for manual supervision suggest caution in clinical settings. The complexity and unpredictability of AI algorithms call for cautious implementation and regular manual validation. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for successful integration into orthodontic practice.

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Section: Treatment Outcome Predictionmentioning

confidence: 99%

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning—A Comprehensive Review

Kazimierczak,

Serafin

et al. 2024

JCM

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“…Additionally, deep learning can lessen the strain on dentists by improving the efficiency of dental follow-up and treatment. 2023 [36] Evaluating the accuracy of automated orthodontic digital setup models.…”

Section: Image Analysis and Diagnosismentioning

confidence: 99%

The Future of Orthodontics: Deep Learning Technologies

Surendran,

Daigavane,

Shrivastav

et al. 2024

Cureus

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Deep learning has emerged as a revolutionary technical advancement in modern orthodontics, offering novel methods for diagnosis, treatment planning, and outcome prediction. Over the past 25 years, the field of dentistry has widely adopted information technology (IT), resulting in several benefits, including decreased expenses, increased efficiency, decreased need for human expertise, and reduced errors. The transition from preset rules to learning from real-world examples, particularly machine learning (ML) and artificial intelligence (AI), has greatly benefited the organization, analysis, and storage of medical data. Deep learning, a type of AI, enables robots to mimic human neural networks, allowing them to learn and make decisions independently without the need for explicit programming. Its ability to automate cephalometric analysis and enhance diagnosis through 3D imaging has revolutionized orthodontic operations. Deep learning models have the potential to significantly improve treatment outcomes and reduce human errors by accurately identifying anatomical characteristics on radiographs, thereby expediting analytical processes. Additionally, the use of 3D imaging technologies such as cone-beam computed tomography (CBCT) can facilitate precise treatment planning, allowing for comprehensive examinations of craniofacial architecture, tooth movements, and airway dimensions. In today's era of personalized medicine, deep learning's ability to customize treatments for individual patients has propelled the field of orthodontics forward tremendously. However, it is essential to address issues related to data privacy, model interpretability, and ethical considerations before orthodontic practices can use deep learning in an ethical and responsible manner. Modern orthodontics is evolving, thanks to the ability of deep learning to deliver more accurate, effective, and personalized orthodontic treatments, improving patient care as technology develops.

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“…Predicting treatment outcomes can help orthodontists analyze and treat malocclusions more scientifically, reducing potential risks and complications during and after clinical treatment. Currently, AI can aid in predicting dental, skeletal and facial changes, as well as patients' experience of clear aligners, thereby guiding the treatment planning [137][138][139][140][141].…”

Section: Treatment Outcome Predictionmentioning

confidence: 99%

“…Orthodontic tooth setup, initially proposed by Kesling, enables the visualization of the treatment progress and final occlusion, but manual tasks like tooth segmentation and reposition are labor-intensive. With the continuous advancements of digital orthodontics and artificial intelligence, automated virtual setups have been widely applied, especially in the field of clear aligners [137]. Woo et al compared the accuracy of three pieces of automated digital-setup software with that of a manual setup regarding six directions of tooth movement [137].…”

Section: Treatment Outcome Predictionmentioning

confidence: 99%

“…With the continuous advancements of digital orthodontics and artificial intelligence, automated virtual setups have been widely applied, especially in the field of clear aligners [137]. Woo et al compared the accuracy of three pieces of automated digital-setup software with that of a manual setup regarding six directions of tooth movement [137]. The results indicated that the pieces of automated virtual-setup software were effective overall, but further manual adjustments may be still required in clinical practice.…”

Section: Treatment Outcome Predictionmentioning

confidence: 99%

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Application of Artificial Intelligence in Orthodontics: Current State and Future Perspectives

Liu,

Zhang,

Shan

2023

Healthcare

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In recent years, there has been the notable emergency of artificial intelligence (AI) as a transformative force in multiple domains, including orthodontics. This review aims to provide a comprehensive overview of the present state of AI applications in orthodontics, which can be categorized into the following domains: (1) diagnosis, including cephalometric analysis, dental analysis, facial analysis, skeletal-maturation-stage determination and upper-airway obstruction assessment; (2) treatment planning, including decision making for extractions and orthognathic surgery, and treatment outcome prediction; and (3) clinical practice, including practice guidance, remote care, and clinical documentation. We have witnessed a broadening of the application of AI in orthodontics, accompanied by advancements in its performance. Additionally, this review outlines the existing limitations within the field and offers future perspectives.

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Evaluating the Accuracy of Automated Orthodontic Digital Setup Models

Cited by 9 publications

References 16 publications

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning—A Comprehensive Review

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning—A Comprehensive Review

The Future of Orthodontics: Deep Learning Technologies

Application of Artificial Intelligence in Orthodontics: Current State and Future Perspectives

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