AI Echo for Tricuspid Regurgitation Severity

Us2.ai’s latest study, presented at ACC.25 in collaboration with The Chinese University of Hong Kong, showcases the development and validation of an AI-driven workflow that integrates multiple echocardiographic parameters to quantify tricuspid regurgitation (TR) severity.

The findings demonstrate that this multiparametric AI workflow delivers fast, accurate, and reproducible TR severity assessments. Performance of the AI models was shown to be comparable to—or in some cases better than—that of three expert cardiologists.

By standardizing transthoracic echocardiographic (TTE) evaluations, the solution has the potential to enhance diagnostic accuracy, risk stratification, and clinical decision-making—marking a significant step forward in advancing precision cardiology.

“This study demonstrates AI’s transformative role in echocardiography. Our automated TR severity assessment achieves diagnostic accuracy comparable to expert cardiologists while delivering superior consistency and efficiency—setting a new standard for precision in valvular heart disease evaluation.”

Prof. Alex Pui Wai Lee & Dr. Lily Zhao
Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong