FSU experts available to discuss the role of artificial intelligence in health care

On Sept. 3, the United States House Committee on Energy and Commerce Subcommittee on Health held a hearing on the critical issue of advancing American health care through artificial intelligence.

Championed by many organizations, including the American Medical Association, the use of AI in health care is seen as one of the new technology’s most important benefits. It is utilized in ways that improve patient health outcomes, provide surgical precision, enhance diagnostic accuracy and much more.

Florida State University’s Zhe He, a professor in the College of Communication and Information and director of the Institute for Successful Longevity, recently developed a study highlighting AI’s impact in diagnostic accuracy, personalized treatment plans, interpreting medical images, streamlining operations and supporting remote patient monitoring among many successful initiatives.

His research lies in the intersection of biomedical and health informatics, artificial intelligence, and big data analytics. He is an elected fellow of the International Academy of Health Sciences Informatics (IAHSI) and the American Medical Informatics Association (AMIA).

“AI has already reshaped health care in tangible ways,” He said of the new technology’s transformative impact. “We now use AI to analyze electronic health records, medical images, and even predict differential diagnosis, mortality and hospital readmissions. These tools don’t replace clinicians, but they extend their reach and help reduce diagnostic delays, personalize treatments and improve efficiency. Importantly, AI is also opening doors to rural communities by enabling new models of remote monitoring and telehealth support.”

Delaney La Rosa, teaching professor at the College of Nursing, is an educator and academic leader whose work bridges clinical practice, digital innovation, and equity-centered curriculum design. She is a nationally recognized researcher and speaker on the ethical application of AI in nursing and education.

La Rosa has expertise in health care informatics, the use of AI in health care and the integration of AI in health care education. She explores how emerging technologies can be aligned with human-centered, accessible approaches to teaching and care.

“The area that AI is transforming health care most is in the preemptive area,” La Rosa said. “We’re finding out when a patient is about to decline or when a patient is about to go septic. We are looking through data across populations.”

“In rural primary care clinics, we know that these areas are stretched for staffing,” she added. “What these AI tools can do is they can use the data across that primary office’s entire population of patients and, using the training that it was trained with, can identify patients who are most likely to develop conditions or who are most likely to benefit from preventive programs.”

Media interested in learning about the multitude of ways AI is advancing health care can reach out to Zhe He at zhe@fsu.edu and Delaney La Rosa at dwl25b@fsu.edu.

Zhe He, professor in the College of Communication and Information and director of the Institute for Successful Longevity

1. We’ve seen enormous impacts already, but what other areas in health care do you feel AI can potentially change in the future?

 I see three big frontiers:

 Patient engagement: Tools that help people better understand their lab results, medications and care plans can empower them to make more informed choices.

 Aging and chronic disease management: With our aging population, AI can play a vital role in predicting risks, supporting caregivers and promoting adherence to treatment.

 Clinical research and drug discovery: AI is accelerating trial recruitment, optimizing study design and uncovering new therapeutic targets. Over the next decade, I think these areas will be transformed just as radiology has been over the past decade.

2. How has AI impacted the work you do?

My research focuses on making health information more accessible and actionable with informatics and AI. For example, my team is developing LabGenie, a GenAI-powered system that helps older adults and caregivers interpret lab test results and generate personalized questions for their clinicians. We are also developing AI-based systems to promote adherence to cognitive training, support post-transplant care and identify strategies for HIV prevention and management for young adults. Across all of this work, AI is not an end in itself—it’s a means to improve patient engagement, adherence to treatment and shared decision making.

Delaney La Rosa, teaching professor, College of Nursing

1. What kinds of advancements has the College of Nursing made as it invests heavily in AI?

From my personal perspective, the biggest contribution we are making for AI is two-fold: The first is we lead the nation. We are the first with a degree in health care AI for our students. There is a big juggernaut out there — we must quickly learn how to use AI and then we must quickly teach our students how to use AI and use it ethically, which is another big issue, and then graduate workforce-ready individuals. Not only do we have our degree program, but we are about to release a microcredential where we develop six total courses for a certificate program called Nursing Essentials of Responsible AI. We are also beginning our postgraduate certificate. We’re leading the nation in graduating. We’re getting workforce-ready students.

 The second thing is we are leading an AI consortium and having our first launch summit that’s happening in Orlando on Sept. 17 – the Nursing and AI Innovation Consortium Launch Summit. And what that means is that we have leaders from across industries — research, practice, higher education — who are coming together, and we’re going to sit at the table and determine where we want to go next in AI.

2. How critical is the role you play in terms of AI education?

 I think the most important thing to me is our foundational essentials course. This course gives you a good grounding in the things that are not going to really change much in AI. It’s that base understanding so we can know the language. One thing that nurses are great at is being able to assess the data and information that’s coming out to see if it’s quality and it’s scientific. But you can’t do that in AI unless you have a basic understanding of how it works.