WILLIAMSBURG — William & Mary has partnered with healthcare technology company Generated Health to develop a next-generation digital nurse using generative AI and reinforcement learning, the university announced.
William & Mary’s Haipeng Chen, an assistant professor of data science, is leading the partnership, according to W&M News. He and his team will develop synthetic patient data to help train a more autonomous version of the company’s digital nurse, “Florence.”
“If we can have an AI system that can deliver automated, personalized management of patients, then we will relieve some of the growing pressures created by the accelerating prevalence of chronic conditions and workforce shortages,” Chen told W&M News.
The contract with Generated Health, starting July 1, will also cover the stipend of a graduate research assistant from Chen’s lab.
The university notes the contract is part of a growing portfolio of externally funded data science research at William & Mary, adding the data science program attracted over $2 million in research funding last year and is now extending its scope with projects supported by federal agencies and the private sector — as well as pursuing technology transfer opportunities.
“As the disciplinary home of AI on campus, the data science unit is particularly interested in studying AI solutions as they impact the world,” Professor Anthony Stefanidis, data science program director, told W&M News, describing the research program as particularly focused on the intersections of data science and AI with location, health, information generation and dissemination, and large-scale experiments and simulations.
The data science program will be part of a proposed new school at William & Mary, which will expand among other things the university’s focus on data fluency and data-intensive research by building on the strengths of existing programs.
According to Generated Health, the digital nurse Florence has already managed over 25 million clinical conversations with 200,000 patients in three countries, delivering a better patient experience and improved clinical outcomes.
“In many cases, patients can’t get an appointment soon enough to get to know their condition better,” said Chen. “Using AI, we can have an automated way to accelerate and augment the current health care system.”
Chen and his team will be developing an AI diffusion model simulating real patient behavior, which will be used to train the nurse model combining generative AI and reinforcement learning. The goal is to develop a next-generation digital nurse with the ability to make effective decisions, learning from its interactions within a set of clinical rules and protocols that eliminate the risk of incorrect information presented as factual.
“I believe that AI should be used for the good: It’s a kind of philosophical belief,” said Chen. “Many people mostly care about the fancy techniques, but then at the end of the day what really makes AI useful is its application to domains related to society.”
“This collaboration is a very important piece of my general vision,” he added. “I would be excited to see this system benefiting tens of thousands or even millions of patients around the world — because that’s one of the end goals for researchers in AI for social good.”
Read the full story at W&M News.
