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Human-AI Collaborative Intelligence for Improving Fetal Flow Management

NCT06371859 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 92

Last updated 2024-05-06

No results posted yet for this study

Summary

This randomized controlled study evaluates the effectiveness of explainable AI (XAI) in improving clinicians' interpretation of Doppler ultrasound images (UA and MCA) in obstetrics. It involves 92 clinicians, randomized into intervention and control groups. The intervention group receives XAI feedback, aiming to enhance accuracy in ultrasound interpretation and medical decision-making.

Objectives:

1. To develop an interpretable model for commonly used Doppler flows, specifically the Pulsatility Index (PI) of the umbilical artery (UA) and middle cerebral artery (MCA), with the aim to provide quality feedback on Doppler spectrum images and suggest potential gate placements.
2. To test the effects of providing Explainable AI (XAI)-feedback for clinicians compared with no feedback on their accuracy in ultrasound interpretation and management.

Conditions

  • Healthy

Interventions

BEHAVIORAL

"XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions"

This study includes 1840 ultrasound images, split into UA and MCA flow and spectrum images, each duplicated for a total of 3680 images to compare explainable AI (XAI) feedback vs. no feedback. The investigators will provide matched sets of 40 images (one for the XAI group and one for the non-XAI group) to participants. Participants are matched based on their level of experience within each hospital (Resident physicians, obstetricians, and gynecologists with obstetric ultrasound experience). All participants are instructed to place gates on the flow images of the umbilical artery and the middle cerebral artery and to assess the quality of the resulting flow curves. Specifically, for flow images, participants must identify the most appropriate gate placement. For spectral flow curves, they are to decide if the curves are of sufficient quality to guide medical management decisions.

Sponsors & Collaborators

  • Slagelse Hospital

    collaborator OTHER

  • Technical University of Denmark

    collaborator OTHER

  • Rigshospitalet, Denmark

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-04-29
Primary Completion
2024-12-01
Completion
2025-12-01

Countries

  • Denmark

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 NCT06371859 on ClinicalTrials.gov