Artificial Intelligence and the Hygienist
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Ann-Marie DePalma, CDA, RDH, MEd
Artificial intelligence refers to the simulation of human intelligence in machines. These machines exhibit human-level, or better, aptitude for learning and problem-solving. From the time they were first conceived in the 1930s and 1940s, it was understood that computers could, theoretically at least, be developed to solve any problem that human intelligence could solve. Building on the work of Alan Turing and other mathematicians in the mid-20th century, "artificial intelligence" emerged as a clearly defined field of research and development by the early 1960s. Early AI research focused primarily on development of problem-solving algorithms. Recognizing the technology's potential, industrial interests, particularly those in military and defense, began pouring significant investments into AI. Their investments did not pay off as hoped, however, and by the 1970s AI innovation had experienced numerous setbacks. Significant processing power, vast quantities of raw training data, and logical learning programs (machine learning algorithms) are essential ingredients for development of effective AI systems. While the early years of AI delivered the necessary machine learning algorithms, processors remained too slow and data resources remained too limited for AI to truly blossom. It wasn't until the rise of the internet and the microprocessor boom of the late 1980s and early 1990s that AI became a truly viable technology.
AI systems today fall into numerous subcategories, each tailored to solve a different sort of problem. These subcategories include predictive analytics that can be used to detect unusual credit card charges or recommend TV shows based on your viewing history; natural language processing that can be used to understand voice commands or provide translations of written text; computer vision that can be used for facial recognition or allowing self-driving cars to stay in their lane; among others. All of these forms of AI have made their way into the dental industry, allowing practices to automate effective communication with patients, evaluate clinical key performance indicators, and improve the accuracy and consistency of radiologic evaluations and periodontal charting. It is in this final area, computer-aided radiology, that AI is poised to deliver the most immediate and profound impact.
The advent of computer vision AI systems—which can read dental radiographs and effectively detect disease and other conditions—gives dentists and their teams a second set of eyes to ensure that every patient's dental radiologic evaluation starts from the best possible place. Clinicians are trained to distinguish between the slight differences in shades of gray that separate healthy dental features from unhealthy ones in a radiographic image. However, even for the most highly trained clinicians, identifying those distinctions can be a challenge. Missing something in a radiograph—or seeing something that isn't there—is not uncommon. Clinicians are human, after all, and while radiologic AI systems are not perfect by any means, they can offer a measure of security against inevitable oversights. Performing radiological evaluations with an AI assistant provides sharper clinical eyes to enhance patient care and improve practice efficiency.
The impact of AI can extend beyond elevating clinical performance, however. AI also offers practices a powerful tool for patient education. Rather than pointing to the slightly lighter gradation at the root indicating an abscess or trying to explain the depth of caries or the level of bone by pointing to specific areas on a radiograph, an AI system can precisely circumscribe and label the problem at hand. This not only makes it far easier for patients to see what is being shown, but also gives patients an objective third-party perspective on the validity of our clinical findings. When patients are better educated about what is going on in their mouths—and when they trust that the clinician's findings are correct—they are far more inclined to accept treatment. Today's dental patients are tech-savvy, and when they see technology backing diagnostic findings, they feel confident investing in the recommended care. Dental hygienists are often crunched for time. Applying AI to assist not only in patient care but also in education efforts can save time while achieving better outcomes for the patient, the clinician, and the practice.
Ann-Marie DePalma, CDA, RDH, MEd
Oral Health Educator
Customer Success Manager for Pearl
Boston, Massachusetts