A review of the use of artificial intelligence in orthodontics

Akdeniz, Berat Serdar; Tosun, Muhammet Emir

doi:10.52142/omujecm.38.si.dent.13

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…Overall, the AI algorithm architecture (CNN, ANN) showed promising results in cephalometric landmark detection and analysis compared with human subjects, as shown in Table 1 . Moreover, 19 articles [ 5 , 6 , 8 , 9 , 10 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ] were excluded from this review, as shown in Supplementary Table S1 .…”

Section: Resultsmentioning

confidence: 99%

Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review

et al. 2022

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This study aimed to analyze the existing literature on how artificial intelligence is being used to support the identification of cephalometric landmarks. The systematic analysis of literature was carried out by performing an extensive search in PubMed/MEDLINE, Google Scholar, Cochrane, Scopus, and Science Direct databases. Articles published in the last ten years were selected after applying the inclusion and exclusion criteria. A total of 17 full-text articles were systematically appraised. The Cochrane Handbook for Systematic Reviews of Interventions (CHSRI) and Newcastle-Ottawa quality assessment scale (NOS) were adopted for quality analysis of the included studies. The artificial intelligence systems were mainly based on deep learning-based convolutional neural networks (CNNs) in the included studies. The majority of the studies proposed that AI-based automatic cephalometric analyses provide clinically acceptable diagnostic performance. They have worked remarkably well, with accuracy and precision similar to the trained orthodontist. Moreover, they can simplify cephalometric analysis and provide a quick outcome in practice. Therefore, they are of great benefit to orthodontists, as with these systems they can perform tasks more efficiently.

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Section: Resultsmentioning

confidence: 99%

Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review

et al. 2022

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“…Apart from that, dental monitoring software that uses AI has proven effective during the treatment phase to track progress, as well as during the retention phase to detect relapse and assess the stability of treatment outcomes, with the benefit of assessing the compliance of patients even without regular in-office visits [41]. After all, the goal of modern technologies is to make dental care high-quality, smooth, time-efficient and cost-effective, with improved treatment planning as well as risk management, and AI certainly adds up to that [46,74,75].…”

Section: Artificial Intelligence Tools and Datasetsmentioning

confidence: 99%

AI and Face-Driven Orthodontics: A Scoping Review of Digital Advances in Diagnosis and Treatment Planning

Tomášik,

Zsoldos,

Oravcová

et al. 2024

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In the age of artificial intelligence (AI), technological progress is changing established workflows and enabling some basic routines to be updated. In dentistry, the patient’s face is a crucial part of treatment planning, although it has always been difficult to grasp in an analytical way. This review highlights the current digital advances that, thanks to AI tools, allow us to implement facial features beyond symmetry and proportionality and incorporate facial analysis into diagnosis and treatment planning in orthodontics. A Scopus literature search was conducted to identify the topics with the greatest research potential within digital orthodontics over the last five years. The most researched and cited topic was artificial intelligence and its applications in orthodontics. Apart from automated 2D or 3D cephalometric analysis, AI finds its application in facial analysis, decision-making algorithms as well as in the evaluation of treatment progress and retention. Together with AI, other digital advances are shaping the face of today’s orthodontics. Without any doubts, the era of “old” orthodontics is at its end, and modern, face-driven orthodontics is on the way to becoming a reality in modern orthodontic practices.

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“… 15 , 16 Machine learning can be used for several important functions in Orthodontics: descriptive, predictive, and prescriptive. 17 , 18 Descriptive functions in Orthodontics can be linked to the formulation of a diagnosis when the different parameters (inputs) are considered 19 . Predictive, as its name implies, is meant to predict the most accurate outcome of a potential treatment - in Orthodontics, it could be the decision to extract or not extract.…”

Section: Architecture Of the Multilayer Perceptron And Of A Simple Ne...mentioning

confidence: 99%

Decoding Deep Learning applications for diagnosis and treatment planning

Retrouvey

Conley

2022

Dental Press J. Orthod.

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Introduction: Artificial Intelligence (AI), Machine Learning and Deep Learning are playing an increasingly significant role in the medical field in the 21st century. These recent technologies are based on the concept of creating machines that have the potential to function as a human brain. It necessitates the gathering of large quantity of data to be processed. Once processed with AI machines, these data have the potential to streamline and improve the capabilities of the medical field in diagnosis and treatment planning, as well as in the prediction and recognition of diseases. These concepts are new to Orthodontics and are currently limited to image processing and pattern recognition. Objective: This article exposes and describes the different methods by which orthodontics may benefit from a more widespread adoption of these technologies.

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A review of the use of artificial intelligence in orthodontics

Cited by 6 publications

References 25 publications

Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review

Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review

AI and Face-Driven Orthodontics: A Scoping Review of Digital Advances in Diagnosis and Treatment Planning

Decoding Deep Learning applications for diagnosis and treatment planning

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