The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice

This study prospectively evaluates whether the performance of an already-developed artificial intelligence (AI) model for predicting spontaneous preterm birth changes when cervical ultrasound images are obtained using different ultrasound image settings. The primary research question is whether the AI model performs differently across images acquired with different imaging settings.

NCT Number	NCT07598097
Lead Sponsor	Rigshospitalet, Denmark Collaborators: Department of Computer Science, University of Copenhagen, Denmark, Technical University of Denmark, Sundhedsdonationer
Conditions	Preterm Birth, Artificial Intelligence (AI) in Diagnosis
Enrollment	2,000 participants
Start Date	2026-03-11
Primary Completion	2027-01 (estimated)
Study Completion	2027-02 (estimated)
Updated on ClinicalTrials.gov	2026-05-20