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How AI is Changing Dentistry

How AI is Changing Dentistry

When Kiss.com launched as a matchmaking site in 1994, artificial intelligence (AI) was still science fiction. Little did we realize how much the early technology would come to change how we shop, how products are delivered, how we choose what to watch, and yes, even how we find our life partners.

Behind the scenes, AI has found its way into nearly every industry, including dentistry.

AI on the business side

On the business side, insurers have been using AI to detect fraudulent claims. For example, Pearl, a dental software firm, uses AI to flag claims that use an x-ray or intraoral scan that is a duplicate or near-duplicate to a previous claim. During a pilot, Pearl’s AI identified up to $6 billion in insurance fraud. And some of the cases were extreme. One provider submitted the same panoramic image to get dentures approved for nearly 40 patients. Pearl was granted a patent in August 2021 for its fraud, waste, and abuse detection abilities.

Clinically, dentists are using AI to improve how they detect and deliver treatment. Intraoral scanning can help select and design better implant restorations that are then manufactured by a 3D printer — often right in the office! AI is also being used to improve caries (cavity) detection and identify problems with radiographs. Technology can even pick up on consistently poor images and prompt an office to re-train its radiographers.

And AI is improving how dentists run their offices, too, automating insurance processing and running website chatbots that can streamline appointment scheduling. Text services send patients reminders or request survey input.

So, what’s next for AI in dentistry?

As more dentists use the technology, it will continue to improve. The increased use of intraoral scanners and digital radiographs is creating larger sets of de-identified data — which machine learning can then process to better identify the need for certain treatments when specific criteria are met. For example, AI can make the correlation that a shadow on a radiograph combined with a certain change in hue on an intraoral picture may indicate a fractured tooth that requires a restoration.

Technology is emerging that may even change how dentists approach soft tissue pathology. Researchers working on salivary diagnostics are developing nano detectors to measure how and when certain biomarkers are secreted. When placed in the oral cavity for frequent sampling, these detectors may spot secretion changes that indicate an emerging disease.

And as technology begins to connect dental conditions with other health markers — even those trackable via wearable sensors — there will be more opportunities for better, earlier treatment. The implications reach far beyond the mouth. After all, periodontal disease can be linked to heart disease and low birthweight babies.

AI for dental career paths

Meanwhile, AI is even being used to help dentists along their career paths.

Dental practice transitions have traditionally been accomplished by a low-tech process, just like dating used to be.

Today’s dentists have more options. And AI can help them explore these options, including ones they may have overlooked — just like how Goodreads may suggest a book that becomes a new favorite.

ADA Practice Transitions (ADAPT) is doing exactly this. ADAPT is helping dentists find the perfect match (whether person or practice), then manage the details to complete a transaction with greater efficiency and success.

As dentistry faces a wave of retirements, integrating AI into practice transitions has the potential to help dentistry achieve better patient retention and dentist satisfaction, while reducing the cost of the average practice transition.

ADAPT starts by asking dentists to fill out an in-depth questionnaire that asks about their preferences. What’s their preferred pace? Which treatments do they like? Do they love having all the latest tech? How do they divide up roles among staff?

These answers help ADAPT’s AI “learn” what matters. Filters process the profiles to show the (human) ADA Advisor several potential matches and rank them according to how well the profiles align. Next, that human advisor validates the suggested matches, applying feedback and additional input to ultimately enhance the matching algorithm with a transition expert’s human touch.

Since ADAPT can show multiple practice styles and locations, they often suggest something that pushes the limits of what someone indicates they are willing to accept, much like Netflix occasionally suggests a seemingly obscure series that you soon find yourself binge-watching. ADAPT then asks for feedback on how well the recommendations fit or flopped. Over time, these responses help the AI to further improve the recommendations for other dentists transitioning with ADAPT.

More inputs, better outputs

The more extensive the network, the better, more valuable, and more efficient the solution becomes for its participants. The classic example is the telephone. One telephone is essentially worthless, but as more people have them, each is more valuable because they can connect with everyone in the network.

Just like caries detection will improve as AI processes more images, machine learning will become more effective at matching ADAPT participants, too. The more matches ADAPT creates, the better they can identify factors that lead to suitable matches.

ADAPT can begin to recognize and rank which attributes are most predictive of successful matches. What’s the right blend of practice size, treatment focus, pace, and patient mix? If two doctors are an 85% match, is that enough to suggest moving forward, or is 70% sufficient to recommend a conversation? The algorithms will begin to “cluster” these traits into groupings of complementary attributes. As more dentists use the service and ADAPT begins to better understand these associations, it will get even easier to help dentists find the right match for their long-term goals.

People remain at the heart of it all

Even as AI begins to streamline the process, you still need humans with the right experience — people who can pick up on nuances that a machine cannot. As AI improves, humans’ roles will shift. While AI may detect a cavity or help make a better implant restoration, it will still take a person to sense a patient’s hesitation and offer a reassuring explanation. On the practice transitions side, AI will free up the advisors to spend more time doing what they do best — advising individual doctors, answering their unique questions, and offering reassurance through a complicated process.

The goal is for AI to complement, not replace humans, so dentists can deliver better care, make better matches, reduce costs, and navigate their work as easily as possible.

 

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