Programs Deploying AI Echo in the Real World
Named implementations of Us2.ai in community screening, primary care, core labs, and hospital cardiology. Each case study traces the clinical pathway, the operators who run it, and the outcomes the program is reporting.
Community Heart Failure Screening in North Liverpool
Everton BEAT Breathlessness Project
BHF-funded · NHS + Everton in the Community
A community diagnostic hub run from Everton in the Community’s People’s Place screens breathlessness in one of England’s most deprived areas. Heart failure nurses and GPs use Us2.ai under cardiologist oversight, with a target of assessment to treatment in 60 minutes.
- 3% new HF in 2024 pilot
- 12% new COPD in 2024 pilot
- 1,500 patients targeted over 12 months
Practice Nurse-Led Heart Failure Screening in Australian Primary Care
PANACEA-HF
MRFF-funded · University of Notre Dame Australia
A federally funded program trains practice nurses to deliver AI-mediated cardiac ultrasound in metropolitan and rural-remote primary care clinics. Early data shows imaging quality rising sharply with structured training, and an algorithm-led triage that outperforms unaided GP referral.
- 96.7% algorithm sensitivity
- 98.8% algorithm specificity
- 700+ patients on track for August 2026 results
Vietnam's First AI Echocardiography Deployment
University of Medicine and Pharmacy Hospital, Ho Chi Minh City
University teaching hospital · Cardiovascular Imaging Unit
The first hospital in Vietnam to apply AI to echocardiography analyzed over 120 studies in its initial deployment. The Cardiovascular Imaging Unit reported a substantial reduction in the time taken to reach a diagnosis, with clinician review and sign-off unchanged.
- First in Vietnam to apply AI to echo
- 120+ studies in initial deployment
- ~10 min diagnosis time reported by the unit
AI Echo Analysis at Brigham's Cardiac Imaging Core Laboratory
Brigham and Women's Hospital · Cardiac Imaging Core Laboratory
Academic core lab · Clinical trials of novel cardiovascular therapies
The CICL at Brigham and Women's Hospital uses Us2.ai to speed echocardiographic analysis for cardiovascular clinical trials, combining automated reads with expert clinician review. Validation in Nature Communications (2022) supports the deployment.
- < 2 min analysis per study (vs ~30 min manual)
- 0 variability between runs on the same study
- 2022 Nature Communications validation
More case studies coming as additional programs publish results. To discuss using Us2.ai in your service, book a demo.