Using deep learning to improve detection of fetal congenital abnormalities
Pattern Recognition and Anomaly Detection in Fetal Morphology Using Deep Learning and Statistical Learning
This study is testing a new smart system to help ultrasound technicians find fetal abnormalities more accurately during pregnancy.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 4000 (estimated) |
| Ages | 18 Years to 50 Years |
| Sex | Female |
| Sponsor | University of Craiova Academic / other |
| Locations | 1 site (Craiova, Dolj) |
| Trial ID | NCT05738954 on ClinicalTrials.gov |
What this trial studies
This observational study focuses on enhancing the detection of congenital abnormalities (CAs) in fetuses through advanced deep learning and statistical learning techniques. By utilizing a specialized intelligent system, the study aims to improve the accuracy of morphology scans, which are crucial for early diagnosis and intervention. The system will assist sonographers in identifying fetal biometric planes and signaling unusual findings, thereby facilitating better decision-making and discussions regarding prognosis with parents. The project integrates various approaches to ensure comprehensive evaluation and aims for direct implementation in clinical practice.
Who should consider this trial
Good fit: Ideal candidates for this study are pregnant women in their second trimester.
Not a fit: Patients who are not pregnant or are in the first or third trimester may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could significantly improve early detection of congenital abnormalities, leading to timely interventions and better outcomes for affected infants.
How similar studies have performed: Other studies utilizing deep learning for medical imaging have shown promising results, indicating potential success for this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Second trimester pregnant women Exclusion Criteria: -
Where this trial is running
Craiova, Dolj
- University Emergency County Hospital — Craiova, Dolj, Romania (Recruiting)
Study contacts
- Principal investigator: Smaranda Belciug, Assoc. Prof. — University of Craiova
- Study coordinator: Smaranda Belciug, Assoc. Prof.
- Email: sbelciug@inf.ucv.ro
- Phone: 729127574
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.