We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.
—Bill Gates, Microsoft Co-Founder1
Dentistry may be on the threshold of an explosion in the use of artificial intelligence (AI). We are already familiar with so many AI functions in our daily life—smart homes, robotics, Alexa, and Siri—as well as the remarkable change taking place in our automobiles and truck transportation, ranging from adaptive cruise control to parking assistance, and even to self-driving vehicles. AI, in its many forms, is taking us into an amazing number of new areas in our daily lives.
Health care is also seeing an explosion in AI use. Rather than dampening or slowing down development, the COVID-19 pandemic experience has only accelerated it, as can be seen with the development of so many clinical decision support tools, predictors, and test and vaccine distribution protocols.
Tim Cook, CEO of Apple, the world’s richest company,2 recently stated, “I really believe that if you zoom out to the future and then look back and ask, ‘What has Apple’s greatest contribution been?’ it will be in the health and wellness area.” Tens of millions of people now wear an Apple Watch device that monitors key health metrics and allows them to share data anonymously with researchers, which many do. Some 400,000 Apple Watch users participated in one Stanford study. This enables scientists, says Cook, to “democratize research by having much larger constituencies that are able to participate.”3
Today, one of the first broadly recognized AI tools in health care, IBM’s Watson, is not only “old news” but also may be the standard of care for radiologist interpretation of images. Dentistry is now experiencing this push into image evaluation using AI. Several firms are offering tools that can be used today and have promise both for improving clinical workflow and for providing diagnostic and, potentially, treatment planning assistance.
A recent systematic review in the Journal of Dental Sciences, published in January 2021, states, “AI models have been used in detection and diagnosis of dental caries, vertical root fractures, apical lesions, salivary gland diseases, maxillary sinusitis, maxillofacial cysts, cervical lymph nodes metastasis, osteoporosis, cancerous lesions, alveolar bone loss, predicting orthodontic extractions, need for orthodontic treatments, cephalometric analysis, age and gender determination.”4
The article goes on to explain that accuracy of AI-derived tools for dentistry is impressive so far. “They mimic the precision and accuracy of trained specialists. In some studies, it was found that these systems were even able to outmatch dental specialists in terms of performance and accuracy.”4
The first robotic dental surgery system was cleared by the Food and Drug Administration (FDA) for dental implant procedures in 2017. At the end of 2017, the world’s first autonomous guided dental implant placement system was developed by Zhao and colleagues in China.5
It is easy to see that the many forms of AI are already having an impact on our profession. This paper will provide a basic understanding of the various forms of AI; furthermore, it will delve into the currently utilized AI areas as well as those that have been predicted, according to Accenture, to be major influencers in health care, including telehealth, workflow assistance, and even cybersecurity.8
There are several current dental AI products and some that are likely imminent.
In the broad sense, AI systems comprise a science that is designed to mimic human intelligence. There are a number of AI subsets, which include machine learning, deep learning, cognitive computing, computer vision, and natural language processing (NLP). Machine learning involves training computing systems to look for hidden patterns in data to build analytical models. Deep learning utilizes more complex neural networks of computing systems that loosely mimic the human brain to discover and analyze complicated patterns in very large “big data” databases. Cognitive computing refers to the use of computer systems to simulate human thought processes. Computer vision uses deep learning to recognize patterns in images and videos. NLP uses AI to recognize speech and written language and to communicate with system users through more commonly used language.
Although behind medical care in development and adoption, dentistry is experiencing a growing number of AI products and substantially more research and development for potential new products. Many are similar to those developed for our medical colleagues, likely because they can be adapted more quickly than products developed from scratch. Thus, the direction of development of dental products using various aspects of AI trend with those gaining adoption in the medical field.
Forbes stated in 2018 that the most important AI areas for health care would be administrative workflows, image analysis, robotic surgery, virtual assistants, and clinical decision support.9 A 2018 report in the Harvard Business Review mentioned the same areas and also included connected machines, dosage error reduction, and cybersecurity.10 A 2019 report from McKinsey and Company states important areas using connected technologies, big data, and AI insights include cognitive devices, electroceuticals, clinical robotics, and robotics for administrative process automation.11
There are several current dental AI products and some that are likely imminent.