In his research, Dr. Jay Patel, is at the forefront of integrating AI into oral health care. Now he’s bringing that expertise and knowledge about AI into the clinic and classroom. His goal? To make training more personalized, objective, and efficient—ultimately improving the learning experience for students and the outcomes for patients.
AT TEMPLE DENTAL, Dr. Jay Patel is uniquely qualified to answer that question. As director of the school’s new AI Center and assistant professor of dentistry, Patel brings two viewpoints to the question. He is both a researcher and an educator.
“It is critical to have both skillsets,” he says. “That means I’m seeing so many things in both education as well as patient care that can be improved, and I have the tools to do something about it.”
In fact, he recently has received several awards. In addition to the William B. Clark Award for his clinical research, he recently received the National Institutes of Health’s High Priority, Short-Term Project Award, or R56. To provide early periodontal disease diagnosis and prevention, the focus is on automatic identification of early bone loss patterns from radiographs invisible to the human eye. And in the educational realm, he’s already testing an AI tool that should be ready for implementation sometime soon.
AI can choose best students
Patel also believes that relying solely on GPA and examination scores is insufficient for admitting students into dental programs. “Dentistry is a patient-centered profession,” he says, “that often involves caring for individuals in pain, where empathy, compassion, and kindness are essential qualities. AI can support the development of new admission metrics that assign appropriate weight to both academic performance and humanistic attributes. That enables the selection of not only academically strong candidates but also individuals best suited to become compassionate and effective future dentists.”
Summing up his reasons for pursuing AI tools in the classroom and clinic, Patel admits he’s always been passionate about education. “I love seeing how technology can help us teach and learn better,” he says.
Dr. Jay Patel
6 critical educational areas for AI development Although his patient care research is first and has been well recognized with awards and funding, he notes that educational research has equal importance. So he is voluntarily pursuing development of the following six areas. Personalized Learning One of his first initiatives is using AI tutors to tailor educational content based on individual performance. He explains: “I’m a visual learner and like to watch videos, but some people just like to read. This system is adaptive. It provides targeted feedback, creating practice questions focused specifically on where students need support in learning certain concepts. Then students can excel in areas where traditional learning may not provide enough help.” Objective assessment and feedback Another application can use AI to compare a student’s work against the ideal and then give immediate feedback that is consistent all the time. Describing what is happening now, Patel says a student’s pre-clinical work is shown to a faculty member who is available at the moment—but who may not be available later. So multiple faculty members may get involved and offer different opinions. Instead, “AI is very objective, which is huge,” he notes. “Subjective feedback leads to frustration, stress, and discouragement in students. Yet, providing consistent feedback through one mechanism reduces frustration and improves productivity in student learning.” Simulation and virtual reality Patel also envisions setting up a virtual reality patient through simulation and then asking students to practice. The model would mimic tongue movement, cheek resistance, nerve positioning and more so they could learn to work with confidence. It would really help students, he says, “because after their second year, students have to jump into clinics, and they’re anxious.” Interdisciplinary learning Connecting dental education to the rest of the healthcare system is yet another area to develop. “I can help bring the two systems together,” he notes. “For example, right now we have to ask patients about their medical history, and all patients may not remember. AI can help us link their dental records with their physician’s medical records. Then we can pull up patients’ up-to-date medical history directly. Because the process is more accurate and efficient, it saves a significant amount of documentation time and provides more time for patient care. The process also leads to safer care.” Administrative tasks AI can also streamline documentation, one of most time-consuming and frustrating parts of clinical education, Patel emphasizes. “Students spend too much time documenting. There is too much information, and it’s redundant. AI can help them document things faster and handle a lot of other administrative work as well.” Practice-based evidence In addition, AI has the potential to shift how students are evaluated. Currently, grading can depend on how many patients a student treats. But Patel believes AI can provide a qualitative measure in addition to the quantitative one. In short, AI can tell us about quality of care. “There’s no grading for whether a student provided the best treatment, at least not to my knowledge,” he says. |
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