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Efficacy Study of DeepDDH System in Screening Infants with Developmental Dysplasia of the Hip (DDH)
Sponsor: RenJi Hospital
Summary
To ascertain the efficacy of the DeepDDH system, a deep learning framework, in enhancing diagnostic accuracy and curtailing follow-up intervals for infants undergoing screening for developmental dysplasia of the hip (DDH), the researchers are executing a blinded, randomized controlled trial. This trial juxtaposes AI-only and AI-assisted assessments of DDH against sonographer interpretations across various proficiency levels in the preliminary analysis of ultrasound images.
Official title: Blinded Randomized Control Trail of Artificial Intelligence-Assisted Ultrasound Screening for Neonatal Hip Dysplasia in a Clinical Cohort
Key Details
Gender
All
Age Range
28 Days - 6 Months
Study Type
INTERVENTIONAL
Enrollment
1976
Start Date
2025-01-15
Completion Date
2025-04-30
Last Updated
2025-01-09
Healthy Volunteers
No
Conditions
Interventions
Junior sonographer measurement of DDH
Participants will not receive visual cues from the DeepDDH system. Junior sonographer technicians will offer preliminary interpretations before these are subjected to validation and subsequent review by expert's team.
Senior sonographer measurement of DDH
Participants will not receive visual cues from the DeepDDH system.
Automated annotation of the DDH measurement through deep learning
Through randomization, a subset of the preliminary interpretations will be conducted by AI technology, and the study team will evaluate the degree of divergence between these AI-generated preliminary interpretations and the final interpretations.
AI-assisted junior sonographer meaturement of DDH
Participants will receive visual cues from the DeepDDH system.
Locations (1)
Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, China