NCT06566014

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

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 38 (actual)
• Sponsor: Copenhagen Academy for Medical Education and Simulation · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Accepted

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.

Conditions

• Spina Bifida

Interventions

Type	Name	Description
OTHER	Evaluation of XAI-assisted spina bifida diagnosis	AI feedback

Timeline

• Start date: 2024-07-01
• Primary completion: 2024-10-30
• Completion: 2024-10-30
• First posted: 2024-08-22
• Last updated: 2024-12-04

Locations

1 site across 1 country: Denmark