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NCT06002412

Quality Control of Ultrasound Images During Early Pregnancy Via AI

Recruiting now Last updated 8 September 2023
What this trial tests

trial testing Image quality control in Early Pregnancy in 400 participants. Currently enrolling.

Timeline
1 September 2023
Primary endpoint
31 December 2023
30 July 2028

Quick facts

Lead sponsorChinese Academy of Sciences
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment400
Start date1 September 2023
Primary completion31 December 2023
Estimated completion30 July 2028
Sites4 locations across China

Drugs / interventions tested

Conditions studied

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.

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Other recruiting trials for Early Pregnancy

Currently open trials in the same condition.

Other Chinese Academy of Sciences trials

Trials by the same sponsor.

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Data sources for this page

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.

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