The Study Aims to Improve the Accuracy of Detecting Spina Bifida During Early Ultrasound Scans. to Achieve This, an AI Model Has Been Developed to Provide Feedback About the Presence of Spina Bifida. a RCT Has Been Designed to Compare the Effectiveness of AI Feedback with No AI Feedback.
Evaluation of XAI-assisted Spina Bifida Diagnosis
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Julie Leth-Petersen
- Phone Number: +4526399590
- Email: julielethp@hotmail.com
Study Locations
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-
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Copenhagen, Denmark
- Copenhagen University Hospital, Rigshospitalet
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Obstetricians
Exclusion Criteria:
- Fetal medicine specialists
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: AI feedback
The participant will receive AI feedback upon completing the task of analyzing 20 images.
The AI feedback will include a prediction (Normal/Spina Bifida) along with a confidence score ranging from 0.0 to 1.0, where 0.0 indicates the lowest confidence and 1.0 indicates the highest confidence.
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AI feedback
|
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Placebo Comparator: No AI feedback
The participants will complete the task of analyzing 20 images without any AI feedback.
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AI feedback
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Evaluation of XAI-assisted spina bifida diagnosis
Time Frame: One month after the survey is distributed.
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The study aims to evaluate whether AI feedback improve the accuracy of diagnosing spina bifida by comparing the number of correct and incorrect responses in a task involving 20 images.
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One month after the survey is distributed.
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Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- P-2019-310
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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