KENNESAW, Ga. | Apr 21, 2026

Led by Assistant Professor of Mechanical Engineering in the , the , 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鈥檚 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.
鈥淭raditionally, these types of simulations can take several hours or even weeks to complete,鈥 Shi said. 鈥淲ith AI, we can reduce that time to milliseconds while still maintaining accuracy.鈥


For Shi, the goal is to create patient-specific models that reflect everyone鈥檚 unique characteristics. The work reflects a broader effort within Kennesaw State to apply engineering principles to real-world health challenges.
鈥淓very patient鈥檚 heart is different, not just in shape but in stiffness and internal structure,鈥 Shi said. 鈥淲e want to build models that capture those differences so doctors can better understand each patient鈥檚 condition.鈥
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鈥檚 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.
鈥淒octors can virtually change the heart鈥檚 structure and test different treatment plans to see what will happen,鈥 Shi said. 鈥淭his allows them to choose the best option before doing the actual surgery.鈥
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鈥檚 commitment to innovation at the intersection of engineering and healthcare.
鈥淭his research highlights the power of interdisciplinary collaboration in addressing global health challenges,鈥 Whitman said. 鈥淏eyond the current hype surrounding Artificial Intelligence, Dr. Shi鈥檚 approach shows a practical application of AI that delivers a meaningful, positive impact on individual health.鈥
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.
鈥淥ur goal is to create a framework that goes directly from medical images to understanding how the heart functions,鈥 he said. 鈥淚f we can do that quickly and accurately, it can help doctors make better decisions and improve patient care.鈥
The research was funded by the National Institutes of Health grant number .
鈥 Story by Raynard Churchwell
Photos by Darnell Wilburn and provided
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