AI In Orthodontics: Potential And Pitfalls

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Artificial intelligence is capable of reshaping industries and revolutionizing the world as we know it. AI and deep learning have lurked in our daily lives without us noticing it. Automated chatbots and self-driven cars have been possible due to advances in the world of AI. Recently, we have seen a lot of debate on the magnificence of language learning models (LLMs) like ChatGPT4.0.

The field of orthodontics has also been at the forefront of a digital revolution. Artificial intelligence implementation has made orthodontists’ lives easier by enhancing multiple steps of orthodontic treatment. However, despite the commendable betterments done by AI in orthodontics, there are certain pitfalls of the system that you should be aware of.

Potential Of AI In Orthodontics

We will start off with the perks of incorporating AI in orthodontics and then discuss the drawbacks. Multiple aspects of teeth correction can benefit from the use of artificial intelligence:

Diagnosis

Time

AI can potentially shorten the time required for diagnosis whilst keeping it accurate and reliable. Where clinicians spend minutes to determine cephalometric landmarks, AI does it in less than a second (per image computational time for programs like YOLOv3 was just 0.05 seconds!).

Diagnostic Imaging

Keeping in mind the significance of diagnostic imaging in orthodontics, AI experts have made special efforts in radiomics. AI programs do a fine job of enhancing poor-quality 2D cephalometric X-rays (reduce noise and improve contrast). It gets along well with the latest intraoral scans.

Several dentists are now shifting from conventional brackets to clear aligners. Digital impressions are paving the way for a saga of modernized orthodontics and AI can be a very useful tool in this transition toward digitalization. Machine learning algorithms help drive different imaging techniques including digital scans, 3D facial images CBCT scans, etc. The integration of AI with digital impressions allows precise and hassle-free treatment planning.

Growth prediction

Determining the period of a patient’s growth is a critical factor in tooth movement. Conventionally, orthodontists have been using techniques like CVM and wrist X-rays to determine the skeletal age. Inexperienced clinicians can make mistakes in stage identification. But, owing to the high accuracy, studies have proven AI+machine learning to be a clinically reliable tool in growth prediction.

Decision-Making

Perhaps the greatest advantage of AI incorporation lies in the decision-making for orthodontic treatment. After deep analysis of the malocclusion, growth stage, and jaw-tooth discrepancies, artificial intelligence provides you with the ideal solution. AI helps orthodontists determine the need for extractions and even maps out the pattern of extraction. Per clinical studies, the algorithms are spot-on and the accuracy of the AI-induced treatment plan is very high (above 93%).

There are AI programs that identify cases ideal for orthognathic surgery. This spares a lot of inter-departmental consultations and precious time. Moreover, AI-based software provides a clear picture of the outcomes. Thus, making the patient and the operator aware of the results.

Patient Monitoring

Clear aligner therapy has opened up new horizons in the field of orthodontics. The AI-based treatment modality has not only made patients’ lives easier but also reduced the burden on dentists. Specialized AI-based smartphone apps let patients inform dentists about the progress of treatment without visiting the facility. Mobile patient monitoring is only possible due to the advancements in AI. Programs like AlignerAi patient app effectively monitors progress, and keeps the data up-to-date. Research shows that there is need for significant improvement in this field.

Research And Development

Clinical trials are the backbone of medical and pharmaceutical breakthroughs. There are numerous implications in handing such a delicate task to artificial intelligence. However, reports suggest that AI integration in clinical trials has promising results and can pave the way for sustainable medical research.

Pitfalls Of AI In Orthodontics

Data Management

Orthodontic clinics carry sensitive and private data of patients. Digitization of data recording makes it prone to leakage and hacking. In the present world, software companies make tireless efforts to secure personal data. The task becomes even more difficult with the incorporation of AI. Thus, ensuring data safety is a major challenge in the field of orthodontics.

Equitability And Bias

Bias is an inevitable phenomenon of medical research and treatment. While human researchers/clinicians can identify and try to minimize bias, any such feature is missing in AI. If the data extracted for machine learning is biased, AI can not figure out a way to eliminate it. Therefore, experts suggest adding ethical metrics into AI programs to reduce bias and increase equitability.

Trust And Transparency

Despite the perks of AI in healthcare, there is a generalized lack of trust by patients in computerized programs. Patients expect to follow the decisions based on the expertise of their doctor. And the use of AI can potentially create a trust-deficit. The result of this weakened relation is poor patient satisfaction.

The black box effect of all AI systems adds to further trust issues. Most AI systems do not reveal how they reached a specific design, keeping the user in the dark. This is known as the black box effect. Thus, the lack of transparency in processing is another pitfall of AI in healthcare.

Implementation Of AI Programs

A large number of orthodontists are adopting AI to improve their practice. However, most clinicians do not consider continuation of quality assurance. Doctors’ training of updating the programs and ensuring regular alterations is important.

Final Word

Artificial intelligence has the potential to revolutionize orthodontics. Machine learning paired with the genius of neural networks aids in speeding up and enhancing diagnosis. AI provides accurate treatment plans and helps orthodontists in selecting patients for orthognathic surgery. The implementation of AI in research may have some implications but has shown promising results in the recent past.

While we are all praise for AI, there are certain implications in the nearly perfect system. Data security is a major concern for AI programs that require extensive safety measures and encryptions. AI-based systems can incorporate bias and the black box effects lead to reduced transparency of the processing. This eventually leads to trust deficit and poor patient satisfaction. However, continuous iterations are underway to mend the problems and refine AI for future dentistry.

References

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