AI Diagnosis of Heart Disease
Clinicians can miss or inconsistently interpret cardiac ultrasound findings, leading to delayed or inaccurate heart disease diagnosis.
An AI-powered system integrated into clinical ultrasound workflows that automates and improves interpretation to identify cardiac disease and assess cardiac function.
Clinicians and enterprise hospitals/health systems that perform and interpret cardiac ultrasound exams.
MD 2014, UCSF Internal Medicine Residency 2017, Stanford Cardiology Fellowship 2020, Stanford Cardiologist, Cedars Sinai Medical Center
PhD Computer Science 2022, Stanford University BS Computer Science 2015, California Institute of Technology