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Safety and Efficacy Study of AI LVEF

NCT05140642 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 3495

Last updated 2022-07-05

No results posted yet for this study

Summary

To determine whether an integrated AI decision support can save time and improve accuracy of assessment of echocardiograms, the investigators are conducting a blinded, randomized controlled study of AI guided measurements of left ventricular ejection fraction compared to sonographer measurements in preliminary readings of echocardiograms.

Conditions

  • Heart Failure, Systolic
  • Heart Failure, Diastolic

Interventions

OTHER

Automated annotation of the left ventricle through deep learning

A semantic segmentation deep learning model will identify the left ventricle and label the left ventricle. The AI model will produce an assessment of LVEF using video based features.

OTHER

Sonographer Measurement of LVEF

Standard practice sonographer measurement of left ventricle and assessment of LVEF

Sponsors & Collaborators

  • Cedars-Sinai Medical Center

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Max Age
110 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-04-01
Primary Completion
2022-06-29
Completion
2022-06-29

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05140642 on ClinicalTrials.gov