Status:
UNKNOWN
Machine Learning-based Anomaly Recognition System
Lead Sponsor:
Assiut University
Collaborating Sponsors:
Middle-East Obstetrics and Gynecology Graduate Education (MOGGE) Foundation
Conditions:
Fetal Anomaly
Eligibility:
FEMALE
18-45 years
Brief Summary
MARS is an artificial intelligence-powered system that aims at detecting common fetal anomalies during real-time obstetrics ultrasound. The current study comprises 2 stages: (1) The stage of model cre...
Detailed Description
Routine second trimester anomaly scan has become a routine part of antenatal care. Early detection of fetal anomalies permits patient counselling, consideration of termination if detected anomalies ar...
Eligibility Criteria
Inclusion
- Pregnant women between 18 and 45 years
- Available ultrasound image with clear findings
- postnatal confirmation of diagnosis
Exclusion
- Absence of research authorization on medical records
Key Trial Info
Start Date :
June 1 2021
Trial Type :
OBSERVATIONAL
Allocation :
ESTIMATED
End Date :
December 1 2023
Estimated Enrollment :
1000 Patients enrolled
Trial Details
Trial ID
NCT04897178
Start Date
June 1 2021
End Date
December 1 2023
Last Update
May 25 2021
Active Locations (2)
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1
Aswan Faculty of Medicine
Aswān, Egypt, 81528
2
Assiut Faculty of Medicine - Women Health Hospital
Asyut, Egypt, 71515