AI’s potential impact is most evident in orthodontic diagnosis, where it has demonstrated promising capabilities in automating labor-intensive processes and improving accuracy.
According to a recent scoping review published in the Journal of Dentistry, multiple studies have demonstrated the use of AI in cephalometric analysis, diagnosis of occlusal features, maturity determination, and upper airway assessment.
For example, some AI models have achieved greater than 90% accuracy in tasks such as cervical maturity staging. Similarly, AI has performed well in diagnosing malocclusion using 2D and 3D imaging, with accuracy rates as high as 99% in certain cases. These advances have significantly reduced the time required for human assessment and the variability inherent in human assessment.
AI advances in treatment planning are equally significant. With its ability to instantly and accurately assess visual information, AI facilitates subsequent assessment steps in the clinical workflow.
In orthodontic treatment planning, AI has proven to be extremely valuable in simplifying complex decision-making processes.
AI models have been used to predict the need for extractions, plan orthognathic surgery, and assist with general orthodontic workflows. The study reported an accuracy rate of over 93% in determining whether tooth extraction was necessary, and the use of 3D imaging enabled precise segmentation of anatomical structures.
In addition, AI models have been developed to simulate treatment outcomes, predict patient experience with braces in terms of pain, anxiety, and quality of life, and prioritize orthodontic issues to address.
Despite the clear and important advantages of AI models, human oversight is still required to ensure their reliability.
A strong driver for the use of AI in dentistry is its ability to complete analytical tasks in a fraction of the time, and ideally, with improved accuracy and efficiency. For example, in orthodontics, tasks such as identifying cephalometric landmarks and staging cervical maturity are time-consuming and prone to human error.
AI models can automate these processes in seconds, with results that are often comparable to those of expert clinicians.
Overall, however, the scientific consensus remains that the accuracy of these models has not yet consistently exceeded expert clinician assessments, a view supported by systematic reviews and professional opinion. Despite the clear and important advantages of AI models, human oversight is still needed to ensure reliability as their diagnostic and analytical capabilities are still developing.
For example, some models excel in simple cases such as fully dentistry patients but struggle with more complex cases such as partially edentulous patients or those with craniofacial anomalies.
Another limitation is that current models rely on 2D radiographic data, which may not accurately reflect 3D anatomy. Despite growing interest in applying AI to 3D imaging, research in this area remains limited.
The importance of retaining human oversight in the increasingly digital world of diagnosis and treatment planning is the subject of a recent article published in Evidence-Based Dentistry, subtitled “Are We Ready to Let Mr. Data Run Our Business?”.
One of the co-authors of the article, Dr. Soumya Narayani Thirumorthy, a board-certified orthodontist at Smile Life Orthodontics in Texas, USA, shared her thoughts on the issue with World Dental Forum: “AI offers significant time savings in braces treatment planning by providing simulations that provide a better starting point for orthodontists to modify and finalize treatment plans.
However, the final decision still lies with the orthodontist as each patient has unique needs that require a personalized treatment plan. Orthodontics is not a one-size-fits-all field and the expertise of human orthodontists is essential to achieve treatment results that best meet the individual needs of each patient.
Therefore, AI should be considered an aid to improve efficiency, but the orthodontist’s experience and ability to adjust treatment plans based on patient feedback remains essential.”
In addition to the efficacy of AI in orthodontics, Dr. Thirumorthy also spoke about the future direction of AI in the field.
“There are still many unexplored areas in our field that could benefit from AI,” she said. “Some of the possibilities include predicting orthodontic relapse in patients and predicting the development of white spot lesions.
I envision a future where AI will be the eyes and ears of orthodontists, assisting with time-consuming tasks such as data analysis, allowing clinicians to use their time more efficiently and focus on direct patient care.”
It seems likely that AI’s already powerful capabilities in orthodontics will continue to improve as its diagnostic and treatment planning algorithms continue to improve. Clinicians are firmly in a position to work together productively with technology in the future.
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