Student investigator: Jooyoung Ryu
Mentored by IDIES member Professor Robert D. Stevens,
Stress Cardiomyopathy (SCM) is an underdiagnosed and frequently misdiagnosed cardiac condition that clinically resembles acute myocardial infarction (AMI) but requires a fundamentally different treatment approach. This project aims to develop a novel labeling strategy for SCM by leveraging echocardiographic characteristics—an essential component of clinical diagnosis. By replacing traditional ICD-based diagnostic codes with echocardiogram-derived labels, we anticipate uncovering a substantial number of previously unrecognized SCM cases. Leveraging this refined label space, we will build machine learning models to identify patients who have SCM and differentiate them from AMI. We hypothesize that this echocardiographic labeling approach will improve predictive performance of SCM detection models compared to the traditional ICD-based labeling approach.
Jooyoung Ryu is a third-year computer science student originally from Seoul, South Korea. He is passionate about AI- and machine learning-driven precision medicine and developing computational tools that improve patient outcomes. With aspirations to attend medical school after graduation, Jooyoung hopes to combine his background in computer science with clinical training to advance healthcare innovation.
