AI And Orthodontics: Bridging The Gap Between Technology And Practice

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Technological advancements are making the world a better place. The advent of new programs and devices helps reduce human labor. The field of healthcare also seems to benefit from the technological renaissance. Orthodontics is a special branch of dentistry that can take advantage of the revolution. However, certain challenges hinder the complete adoption of technology into routine practice.

Luckily, an important runner in the race of technological revolution is artificial intelligence. AI with deep learning can ensure a smooth transition from manual working to automation and easily bridge the gap between technology and practice. Let’s have a look at how AI overcomes the challenges and helps regularize the use of tech in orthodontic practice.

Challenges In Technology Implementation And How AI Can Help

Data Storage And Access

As the healthcare industry is moving towards precision medicine, doctors require loads of data to devise custom-tailored treatment plans. Modern doctors extract data from various sources including:

  • Smartphones
  • Medical sensors
  • Smart devices (wearables, etc.)
  • Consumer apps

The storage of this data is a job that is easier said than done. Orthodontic clinics would require multiple specialized storage devices or a lot of cloud storage to store all of this data, if not for AI-based programs. Manually storing scores of data is cumbersome and time-consuming. Moreover, accessing the data is another problem. Big clinics and hospitals also have to deal with data from pharmacies, labs, and diagnostic departments (cephalometric X-rays for orthodontists). Thus, there has to be quick and easy access for a smooth collaboration between different departments. A lack of optimal storage and quick access to data leads to interoperability issues. AI offers to-the-point solutions and sustainable data storage.

Additionally, for technological adoption, there needs to be good communication between different departments of healthcare. Orthodontists frequently interact with oral surgeons for orthognathic surgeries. This interaction depends on the sharing of diagnostic/clinical data and the exchange of ideas. Generally, there is a lack of integration due to differences in the types of software used. AI provides a universal communication platform for doctors. Thus, it can solve interoperability issues by providing effective big data analytics and data mining. Studies show that artificial intelligence-based systems are being introduced to improve the efficacy of digital healthcare.

Data Security

Another issue closely related to the storage of large amounts of data is security and privacy. Implementing technology means delivering large amounts of sensitive data to the computer. Thus, data safety becomes a major issue that widens the gap between technology and routine practice. Many doctors are reluctant to rely on conventional computerized systems. This is because cybercrime continues to pose a serious threat to the healthcare industry. Cyberattacks on multiple healthcare organizations have led to severe consequences in the past including financial losses, compromises in patient privacy, and reputational damages.

Luckily, AI can help in this regard too. The incorporation of AI programs can keep cyberattacks at bay. According to a study, AI algorithms can identify security breaches and analyze threat intelligence feeds to stay safe and up-to-date. It can also point out the root cause of security breaches to improve security in the future.

Strong AI-driven machine learning models aptly predict cyber-attack behaviors and provide meaningful insights to stay safe. Thus, AI can help keep vast amounts of patient data safe and secure.

Remote Monitoring (Tele-orthodontics)

One of the greatest innovations in digital healthcare is tele-orthodontics. Modern orthodontic patients receiving clear aligner therapy can inform the doctor about their treatment progress without visiting the clinic. This has been possible only due to the accurate and highly efficient AI-based dental monitoring programs. The latest study concludes that remote dental monitoring (eMonitoring) is a reliable option for clinical assessment in guiding clear aligner treatment.

Orthodontists can rely on smartphone-based apps for the acquisition of treatment data. Another study showed that artificial tracking algorithms accurately tracked tooth movement and constructed 3D digital models to a clinically acceptable degree. Therefore, AI is playing its part in bridging the gap between technology and orthodontic practice.

Economic Challenges

When adopting new systems orthodontists consider the economic challenges. Though artificial intelligence requires some investment, the return on investment (ROI) of such funding is promising. Implementation of tech requires acquiring advanced equipment like 3D scanners and digital orthodontic tools. The investment pays you back as these systems greatly enhance patient outcomes. The increase in efficiency with digital devices provides long-term benefits in treatment planning/implementation and patient satisfaction.

Consistency And Quality Control

One of the concerns of consultants in tech adoption is the consistency of programs in providing treatment plans for patients. Achievement of predictable results is only possible if artificial intelligence evolves with changes in patient conditions. Automated systems for dental monitoring treatment progress help maintain consistency. Experts are now investing effort and time in generative AI that aims to create new healthcare data (text, images, etc.). This subfield of AI is expected to revolutionize healthcare in the future.

The most appreciable feature of artificial intelligence is that it continuously evolves and improves with every iteration. By feeding new data to machine learning, AI algorithms evolve with new learning and ensure accurate treatment plans for changing conditions.

Final Word

The adoption of tech in orthodontic practice can improve efficiency and enhance patient outcomes. However, there are some challenges in the shift towards automated working. Artificial intelligence can overcome the major challenges and effectively bridge this gap between technology and practice.

The most prominent obstacle is data storage and management. AI and deep learning models allow easy data storage and quick access. This feature also aids in resolving interoperability issues. The advanced AI algorithms also protect healthcare data against cyberattacks, thereby, ensuring patient data security and privacy. The advancements in artificial intelligence provide superior dental monitoring facilities. This allows the orthodontists to monitor clear aligner patients with ease.

Many orthodontists are reluctant to adopt modern programs due to the investment but with AI there is a great return on investment and superior patient outcomes too. As AI continues to evolve with every iteration, it also ensures consistency of treatment options for the future.

References

  1. Henry, J., & Halil, M. (2024). Sustainable Data Storage for AI Applications: Securing Critical Information for Environmental Responsibility (No. 12214). EasyChair.
  2. Razzaque, A., & Hamdan, A. (2021). Artificial intelligence based multinational corporate model for EHR interoperability on an e-health platform. Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications, 71-81.
  3. https://www.tebra.com/theintake/practice-operations/medical-news/the-major-cyberattacks-that-have-affected-healthcare-systems-in-2024
  4. Telo, J. (2017). Ai for enhanced healthcare security: an investigation of anomaly detection, predictive analytics, access control, threat intelligence, and incident response. Journal of Advanced Analytics in Healthcare Management, 1(1), 21-37.
  5. AlZubi, A. A., Al-Maitah, M., & Alarifi, A. (2021). Cyber-attack detection in healthcare using cyber-physical system and machine learning techniques. Soft Computing, 25(18), 12319-12332.
  6. Tahir, A. (2024). Optimizing Orthodontic Clear Aligner Treatment with Artificial Intelligence Driven Dental Monitoring (Doctoral dissertation, University of Illinois at Chicago).
  7. Homsi, K., Snider, V., Kusnoto, B., Atsawasuwan, P., Viana, G., Allareddy, V., … & Elnagar, M. H. (2023). In-vivo evaluation of Artificial Intelligence Driven Remote Monitoring technology for tracking tooth movement and reconstruction of 3-dimensional digital models during orthodontic treatment. American Journal of Orthodontics and Dentofacial Orthopedics, 164(5), 690-699.
  8. Yu, J. H., Kim, J. H., Liu, J., Mangal, U., Ahn, H. K., & Cha, J. Y. (2023). Reliability and time-based efficiency of artificial intelligence-based automatic digital model analysis system. European Journal of Orthodontics, 45(6), 712-721.
  9. Thakur, N. (2024). Evolution of Generative AI in Healthcare. In Revolutionizing the Healthcare Sector with AI (pp. 26-53). IGI Global.

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