NIH-funded research uses AI to accelerate heart disease diagnosis and treatment

KENNESAW, Ga. | Apr 21, 2026

Lei Shi
Lei Shi
What if doctors could determine heart health before ever stepping into the operating room? At Kennesaw State University, researchers are using artificial intelligence to do just that, transforming how heart disease is diagnosed and treated.

Led by Assistant Professor of Mechanical Engineering Lei Shi in the Southern Polytechnic College of Engineering and Engineering Technology, the $522,695 project, funded by the National Institutes of Health, explores how generative AI can be integrated with biomechanical heart modeling to improve the diagnosis and treatment of heart disease.

The research focuses on analyzing 3D medical images of the heart and using AI to predict how it functions. Traditional heart modeling relies on computational methods that divide the heart into millions of small elements, requiring significant processing time. Shi’s approach uses AI trained on thousands of simulations to replicate those calculations almost instantly, allowing the system to move from raw medical images to functional analysis in a fraction of the time.

“Traditionally, these types of simulations can take several hours or even weeks to complete,” Shi said. “With AI, we can reduce that time to milliseconds while still maintaining accuracy.” 

3D Heart Image
3D Heart Image
Models of a patient's heart
At the core of the project is a process that transforms standard medical scans, such as CT or MRI images, into detailed computational models of a patient’s heart. These models go beyond visualization, allowing researchers to simulate how the heart moves, how stiff the tissue is, and where stress is concentrated during each heartbeat.

For Shi, the goal is to create patient-specific models that reflect everyone’s unique characteristics. The work reflects a broader effort within Kennesaw State to apply engineering principles to real-world health challenges.

“Every patient’s heart is different, not just in shape but in stiffness and internal structure,” Shi said. “We want to build models that capture those differences so doctors can better understand each patient’s condition.” 

The speed of this process has important implications for patient care. By delivering faster insights, clinicians can make more informed decisions and respond more quickly to a patient’s condition.

The technology also allows doctors to test treatment options before performing surgery. By simulating different approaches, physicians can evaluate how the heart would respond without putting the patient at risk.

“Doctors can virtually change the heart’s structure and test different treatment plans to see what will happen,” Shi said. “This allows them to choose the best option before doing the actual surgery.” 

The project is supported through collaboration with clinicians at Emory University, who provide medical imaging data and help validate the models against real patient outcomes. Access to this data remains one of the most significant challenges in the field, making the partnership critical to the research.

SPCEET Dean Lawrence Whitman said the project highlights the college’s commitment to innovation at the intersection of engineering and healthcare.

“This research highlights the power of interdisciplinary collaboration in addressing global health challenges,” Whitman said. “Beyond the current hype surrounding Artificial Intelligence, Dr. Shi’s approach shows a practical application of AI that delivers a meaningful, positive impact on individual health.”

Beyond its clinical applications, the project is also creating opportunities for Kennesaw State students. Undergraduate researchers are contributing to data processing and model development, gaining hands-on experience in a rapidly evolving field.

Shi said the long-term goal is to create a complete, end-to-end system that connects medical imaging directly to mechanical analysis, making advanced modeling tools more accessible in clinical settings.

“Our goal is to create a framework that goes directly from medical images to understanding how the heart functions,” he said. “If we can do that quickly and accurately, it can help doctors make better decisions and improve patient care.” 

The research was funded by the National Institutes of Health grant number 1R15HL181637-01.

– Story by Raynard Churchwell

Photos by Darnell Wilburn and provided

Related Stories

A leader in innovative teaching and learning, Kennesaw State University offers undergraduate, graduate, and doctoral degrees to its more than 51,000 students. Kennesaw State is a member of the University System of Georgia with 11 academic colleges. The university's vibrant campus culture, diverse population, strong global ties, and entrepreneurial spirit draw students from throughout the country and the world. Kennesaw State is a Carnegie-designated doctoral research institution (R2), placing it among an elite group of only 8 percent of U.S. colleges and universities with an R1 or R2 status. For more information, visit kennesaw.edu.