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Juhwan Lee, Ph.D.

Assistant Professor, Biomedical Engineering VCU College of Engineering

  • Richmond VA

Dr. Juhwan Lee’s research focuses on artificial intelligence, medical image analysis, and their applications in cardiovascular medicine.

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Biography

I am an Assistant Professor of Biomedical Engineering at VCU with significant experience in medical image processing, machine/deep learning, and their clinical applications. My research focuses on developing AI methods for intravascular imaging, coronary computed tomography angiography, coronary artery calcium scoring, and chest X-ray analysis to predict short- and long-term cardiovascular outcomes. As a translational scientist, I have more than a decade of experience conducting interdisciplinary research that helps cardiologists and radiologists make more informed treatment decisions. Currently, I serve as Principal Investigator on multiple NIH-funded projects. My long-term goal is to develop interpretable AI models that improve personalized cardiovascular care and patient outcomes.

Industry Expertise

Medical Devices

Areas of Expertise

Cardiology
Artificial Intelligence
Machine Learning & Deep Learning
Medical Image Analysis

Education

Case Western Reserve University

Postdoctoral fellowship

Biomedical Engineering

2020

Dongguk University

Ph.D.

Biomedical Engineering

2015

Research Grants

Cardiovascular risk prediction from AI analysis of coronary calcifications

NIH

2025-08-15

We will create software for predicting cardiovascular health from a low-cost (no-cost) CT calcium score examination, which shows calcifications in the coronary arteries. We will use artificial intelligence to greatly improve the existing CT calcium score method, creating a method that physicians and patients can use in shared decision-making to personalize interventions.

Multi-modality evaluation of high-risk coronary atherosclerotic plaque

NIH

2024-09-01

We will develop methods for the non-invasive, quantitative evaluation of coronary artery disease in computed tomography angiography images. With success, our research will lead to improved detection of coronary artery disease and evaluation of its severity, paving the way for personalized treatments.