Spina Bifida
Conditions
Brief summary
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.
Detailed description
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 randomized controlled trial (RCT) has been designed to compare the effectiveness of AI feedback with no AI feedback. Forty fetal medicine specialists are randomly assigned to receive either the AI feedback or no feedback, and the two groups are compared to determine if the feedback improved the accuracy of detecting spina bifida.
Interventions
OTHEREvaluation of XAI-assisted spina bifida diagnosis
AI feedback
Sponsors
Copenhagen Academy for Medical Education and Simulation
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Investigator)
Eligibility
Sex/Gender
ALL
Healthy volunteers
Yes
Inclusion criteria
* Obstetricians
Exclusion criteria
* Fetal medicine specialists
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Evaluation of XAI-assisted spina bifida diagnosis | One month after the survey is distributed. | 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. |
Countries
Denmark
Outcome results
None listed