I supervise several hundred cardiac stress tests a year and interpret the ECGs that come out of them. These projects are what happens when that clinical judgment meets code.
Lead II · 100 Hz · sinus rhythm at 60 bpm
Background
I am an ACSM Certified Clinical Exercise Physiologist at UW Medicine, where I direct exercise stress echocardiograms and treadmill tests for high-risk cardiac patients. Day to day that means interpreting arrhythmias and conduction abnormalities, screening for contraindications, and deciding in real time whether a test continues.
I hold a master's in clinical exercise physiology and am completing a master's in information management with an emphasis in data science at the University of Washington. The projects below are where clinical knowledge and data science intersect. I understand these problems from the bedside, and I am building the methods to solve them rigorously.
A machine learning system that reads an ECG and flags what warrants a clinician's attention. Version one detects atrial fibrillation; the roadmap extends to ischemic ST changes, conduction abnormalities, and ECGs captured as photographs.