Seoul, South Korea

Hyeong Jun Lee

This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Yonsei University. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Hyeong Jun Lee. Retrieved from https://idiyas.com/inventor/hyeong-jun-lee

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Hyeong Jun Lee: AI-Based Prediction of Coronary Artery Lesions

Introduction

Hyeong Jun Lee is an inventor based in Seoul, South Korea, whose patent work concerns artificial intelligence in cardiovascular medicine. His disclosed invention focuses on improving the prediction of coronary artery lesions using fractional flow reserve (FFR).

Latest Patents

Lee is associated with 1 patent: “Optimization System and Method of AI Algorithm for Prediction Coronary Artery Lesions Based on FFR.” The disclosure describes an optimization system and method for an AI algorithm designed to predict coronary artery lesions based on FFR, with the aim of improving the algorithm’s FFR prediction accuracy.

Career Highlights

Lee is associated with Yonsei University. His patent reflects work at the intersection of artificial intelligence and coronary artery assessment.

Collaborations

The provided information identifies Young Woo Kim and Joon Sang Lee as Lee’s coworkers. Their specific roles in the patent or related research are not stated.

Conclusion

Hyeong Jun Lee’s disclosed patent work applies AI algorithm optimization to FFR-based prediction of coronary artery lesions, connecting his work with medical technology research at Yonsei University.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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