In recent years, there has been much talk about the potential of artificial intelligence (AI) in various industries, including healthcare. As orthodontists, we may feel our profession needs to be more personal and rely on human interaction to benefit from AI. However, people and AI can make great business partners in our field and greatly enhance our ability to provide quality patient care.
Shervin Khodabandeh, a machine learning expert, discusses four categories of human-AI combinations in his TED talk: the recommender, the illuminator, the evaluator, and the optimizer feedback loops. Let’s explore how these categories apply to orthodontic practice and how AI can help us provide better care.
Recommender
As orthodontists, we recommend treatment and appliances to our patients based on their needs and preferences. AI can help us make more accurate recommendations by analyzing large amounts of data on patient outcomes and treatment options. This feedback loop can help us tailor our advice to each patient’s unique situation and increase the likelihood of success. For example, an AI-powered treatment planning software could analyze a patient’s facial pattern, skeletal structure, teeth alignment, and other factors to recommend the best treatment plan. This saves us time and improves our recommendations’ accuracy, ultimately leading to better patient outcomes. Empowered with a vast amount of orthodontic literature, best practices, and treatment data sets, a recommendation engine could be an amazing partnership between clinician and their AI co-pilots.
Illuminator
The illuminator feedback loop involves using AI to provide insights and information to the orthodontist. For example, an AI-powered tool can analyze a patient’s medical history and provide important information we may not have otherwise known. Having additional insights into patient history can help us make more informed decisions about treatment options and avoid potential complications. There are risks and benefits to orthodontic treatment. A review of a patient’s dental history, diagnostic records, and other insights could help illuminate the best course of treatment. In addition, it help us avoid challenges in treatment outcomes and extended treatment. We can also illuminate business metrics, which can run analytics of our practice performance and provide insights into business metrics that can improve our businesses and patient care.
Evaluator
The evaluator feedback loop uses AI to evaluate treatment outcomes and adjust our approach accordingly. For example, AI-powered software can analyze a patient’s progress and alert us to any issues that may arise during treatment. Evaluation and monitoring can help us intervene early and prevent more serious problems from developing. With current virtual monitoring tools, we see the evaluator feedback loop in clinical use and help guide clinical decisions and warning signs with poor oral hygiene, compliance, and response to treatment.
Optimizer
Finally, the optimizer feedback loop involves using AI to optimize treatment plans and improve patient outcomes. For example, AI-powered software can analyze patient data. Furthermore, it can recommend changes to the treatment plan to ensure the best possible results. Large patient data sets can help develop optimized treatment plans to reduce treatment times, gain efficiency, and improve outcomes. Producing appliances optimized by historical data can help us provide more effective care, improve business performance, and increase patient satisfaction.
Conclusion
People and AI can make great business partners in orthodontic practice. By using AI to analyze data, provide insights, evaluate outcomes, and optimize treatment plans, we can offer better care to our patients and improve their overall health and well-being. Of course, AI should not replace the personal touch and human interaction essential to our profession. However, incorporating AI into our practice can enhance our ability to provide quality care. It also helps in staying ahead of the curve in a rapidly changing industry.
