Clinical exercise physiologist · Data scientist

Reading hearts, then teaching machines to.

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.

Projects

ECG Screening Toolkit

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.

Status
v1 live at ecg.bentileo.tech
Stack
Python · scikit-learn · Streamlit · Supabase · nginx
Data
PTB-XL — 21,799 clinical ECGs, 18,869 patients
Period
2026

The Price of a Heartbeat

What US insurers pay hospitals for cardiac rehab and stress testing, and what more patients and more sessions are worth to a program.

Status
Beta dashboard live
Stack
Python · DuckDB · SQL · JavaScript
Data
Hospital price transparency files (July 2026), CDC Atlas of Heart Disease and Stroke (Medicare, 2019–2020), CMS OPPS 2026
Period
2026