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NCT06002412
Quality Control of Ultrasound Images During Early Pregnancy Via AI
trial testing Image quality control in Early Pregnancy in 400 participants. Currently enrolling.
31 December 2023
Quick facts
| Lead sponsor | Chinese Academy of Sciences |
|---|---|
| Status | Recruiting now |
| Study type | OBSERVATIONAL |
| Enrollment | 400 |
| Start date | 1 September 2023 |
| Primary completion | 31 December 2023 |
| Estimated completion | 30 July 2028 |
| Sites | 4 locations across China |
Drugs / interventions tested
- Image quality control
Conditions studied
- Early Pregnancy — all drugs for Early Pregnancy →
Sponsor
Chinese Academy of Sciences — full company profile →
Who can join
20 and older, female only, with Early Pregnancy. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
This research integrates artificial intelligence to enhance early pregnancy ultrasonography quality control, focusing on specific fetal sections. In collaboration with prominent medical institutions, the investigators have amassed extensive fetal ultrasound data. The investigators aim to develop a deep learning model that can accurately identify essential anatomical areas in ultrasound images and evaluate their quality. This tool is expected to significantly decrease misdiagnoses of conditions like Down Syndrome and neural system deformities by ensuring real-time image quality assessment.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT06002412
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
Related trials
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Currently open trials in the same condition.
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06002412 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Chinese Academy of Sciences
- Last refreshed: 8 September 2023
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06002412.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing