Condition: Early Pregnancy · Sponsor: Chinese Academy of Sciences
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.
This description comes directly from the study's public registry record.
Di Dong, Ph.D · +86 13811833760 · di.dong@ia.ac.cn
Yali Zang, Ph.D · yali.zang@ia.ac.cn
Always discuss trial participation with your own doctor first.
| Beijing Obstetrics and Gynecology Hospital affiliated to Capital Medical University | Beijing, China | Recruiting |
| Peking University Third Hospital | Beijing, China | Recruiting |
| Changsha Hospital for Maternal and Child Health Care | Changsha, China | Recruiting |
| Second Xiangya Hospital of Central South University | Changsha, China | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06002412