Federated Learning for Point-of-Care Cardiac Ultrasound
Public ClinicalTrials.gov record NCT07800962. Field values are reproduced from the official study page; the official ClinicalTrials.gov record remains the source of truth for eligibility, enrollment, and contact information.
Data is sourced from official ClinicalTrials.gov public API records. Always review the official ClinicalTrials.gov record for the latest information.
Official title
A Prospective Multicenter Clinical-Performance Study of Federated Machine Learning for Automated Interpretation of Point-of-Care Cardiac Ultrasound
Brief summary
Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.
This prospective, multicenter study will evaluate a federated machine-learning system designed to analyze focused cardiac point-of-care ultrasound examinations. Federated learning allows participating clinical sites to contribute to model development while keeping raw ultrasound images and directly identifiable patient information within each site's controlled computing environment. Encrypted model updates, rather than patient images, will be transmitted for secure aggregation. The prospective validation cohort will include approximately 3,000 adults undergoing clinically indicated focused cardiac ultrasound. Model performance will be compared with an expert interpretation of a comprehensive transthoracic echocardiogram performed within 24 hours. The primary objective is to determine how accurately the model identifies reduced left ventricular systolic function, defined as a left ventricular ejection fraction below 40%. During the initial validation period, the investigational software will operate in silent mode. Its results will not be displayed to treating clinicians and will not be used to diagnose participants, select treatment, or replace standard clinical interpretation. The study will also evaluate image-quality classification, cardiac-view recognition, performance across clinical sites and ultrasound systems, model calibration, processing time, cybersecurity, privacy resilience, and performance across demographic and clinical subgroups. Long-term monitoring will assess whether model performance changes as clinical populations, ultrasound equipment, acquisition practices, and software environments evolve during the 2026-2037 study period.
Study identification
- NCT ID
- NCT07800962
- Recruitment status
- Enrolling by invitation
- Study type
- Observational
- Phase
- Not listed
- Enrollment
- 3,000 participants
Conditions and interventions
Conditions
- Ventricular Dysfunction, Left
- Ventricular Function, Left
- Echocardiography
- Ultrasonography
- Point-of-Care Systems
- Heart Function Tests
- Stroke Volume
- Federated Learning
- Machine Learning
- Artificial Intelligence (AI)
- Deep Learning
- Neural Networks, Computer
- Image Interpretation, Computer-Assisted
- Diagnosis, Computer-Assisted
- Sensitivity and Specificity
- ROC Curve
Interventions
- Focused Cardiac Point-of-Care Ultrasonography Diagnostic Test
- FL-POCUS Federated Machine-Learning Analysis System Device
Diagnostic Test · Device
Eligibility (public fields only)
- Age range
- 18 Years and older
- Sex
- All
- Healthy volunteers
- Healthy volunteers not accepted
This page does not interpret eligibility. Detailed inclusion and exclusion criteria are on the official ClinicalTrials.gov record.
Study timeline
- Start date
- Aug 30, 2026
- Primary completion
- Sep 30, 2036
- Completion
- Sep 29, 2037
- Last update posted
- Sep 1, 2026
2026 – 2037
United States locations
- U.S. sites
- 1
- U.S. states
- 1
- U.S. cities
- 1
| Facility | City | State | ZIP | Site status |
|---|---|---|---|---|
| Truway Health, Inc. | New York | New York | 10016 | — |
Site contact phone numbers, emails, and investigator names are intentionally not displayed here. Open the official ClinicalTrials.gov record for site contact information.
About this trial record page
- What this page shows
- Public field values for ClinicalTrials.gov record NCT07800962, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.
- What this page does not do
- No medical advice, eligibility judgments, treatment recommendations, study quality scoring, or AI-generated medical summaries. No site contact phone numbers, emails, or investigator names.
- Where the data comes from
- Sourced from the official ClinicalTrials.gov public API. The official record is the source of truth.
- Last refresh
- Last update posted Sep 1, 2026 · Synced Sep 2, 2026
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Open the official record
The complete protocol, eligibility criteria, and contact information for NCT07800962 live on ClinicalTrials.gov.