Artificial Intelligence for Learning Point-of-Care Ultrasound

April 23, 2026 updated by: Andre Kumar, Stanford University

Use of Artificial Intelligence for Acquisition of Limited Echocardiograms

Point-of care-ultrasonography has the potential to transform healthcare delivery through its diagnostic and therapeutic utility. Its use has become more widespread across a variety of clinical settings as more investigations have demonstrated its impact on patient care. This includes the use of point-of-care ultrasound by trainees, who are now utilizing this technology as part of their diagnostic assessments of patients. However, there are few studies that examine how efficiently trainees can learn point-of-care ultrasound and which training methods are more effective. The primary objective of this study is to assess whether artificial intelligence systems improve internal medicine interns' knowledge and image interpretation skills with point-of-care ultrasound. Participants shall be randomized to receive personal access to handheld ultrasound devices to be used for learning with artificial intelligence vs devices with no artificial intelligence. The primary outcome will assess their interpretive ability with ultrasound images/videos. Secondary outcomes will include rates of device usage and performance on quizzes.

Study Overview

Status

Enrolling by invitation

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

150

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • California
      • Stanford, California, United States, 95403
        • Stanford University School of Medicine

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Internal medicine residents rotating on the general inpatient wards service.

Exclusion Criteria:

  • Residents who had taken an ultrasound elective offered by our residency program

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Artificial Intelligence Group
Other: Ultrasound with Artificial Inteligence Engabled
Participants shall be randomized 1:1 to receive personal access to a handheld ultrasound device with artificial intelligence vs a device with no artificial intelligence. The groups shall not cross over in which intervention they received.
Active Comparator: Non Artificial Intelligence Group
Other: Ultrasound without Artificial Intelligence Enabled
Participants shall be randomized 1:1 to receive personal access to a handheld ultrasound device with artificial intelligence vs a device with no artificial intelligence. The groups shall not cross over in which intervention they received.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Time to acquire cardiac ultrasound images
Time Frame: During procedure (300 seconds)
This will be measured as the time to acquire a cardiac ultrasound image on a standardized patient, measured in seconds.
During procedure (300 seconds)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Assessment of the quality of captured images
Time Frame: During procedure (300 seconds)
Participants will acquire cardiac ultrasound images on a standardized patient. Two reviewers will review the images and provide a numerical assessment of image quality based on the Rapid Assessment for Competency in Echocardiography (RACE) Scale. This is a 0-20 point scale, with higher scores denoting higher image quality (e.g. a better quality image).
During procedure (300 seconds)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Stanford University

Investigators

  • Principal Investigator: Andre D Kumar, MD, Stanford University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 1, 2021

Primary Completion (Estimated)

December 30, 2026

Study Completion (Estimated)

December 30, 2027

Study Registration Dates

First Submitted

May 31, 2023

First Submitted That Met QC Criteria

June 9, 2023

First Posted (Actual)

June 12, 2023

Study Record Updates

Last Update Posted (Actual)

April 29, 2026

Last Update Submitted That Met QC Criteria

April 23, 2026

Last Verified

April 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • IRB-42094

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Education, Medical

Clinical Trials on Ultrasound with Artificial Inteligence Engabled

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Montenegro

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Subscribe