Prospective Clinical Data Collection for Developing Machine Learning-assisted Obstetric Ultrasound (MOBUS) Screening Algorithms
Prospective Clinical Data Collection for Developing Machine Learning-assisted Obstetric Ultrasound (MOBUS) Screening Algorithms
The goal of this clinical trial is to
Consented participants will be asked to take part in a research ultrasound scan
In this study pregnant and no pregnant subjects will be recruited from Obstetrics and Gynecology clinics/hospitals or from Maternal and Fetal Medicine centers. The pregnant subjects will be in Group 1 and non pregnant subjects will be in Group 2. Pregnant subjects are only recruited if they are scheduled for an obstetric standard of care scan . Both the group will undergo research scan, which is a sweep protocol using handheld FDA approved ultrasound device like Vscan. Patient chart history (no PHI), standard of care scan ultrasound images (no PHI), and research scan ultrasound images (no PHI) would be obtained from Group 1 subjects. Patient history (no PHI), research ultrasound images (no PHI) would be obtained from Group 2 subjects The data collected from this study will be used by the sponsor to develop algorithms for screening various fetal health parameters such as gestational age, placenta location, fetal heart rate, number of fetuses, fetal positions etc
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Inclusion Criteria:
Pregnant group (Group 1)
Non-pregnant group (Group 2)
Exclusion Criteria:
- 1. Participants for whom participating in this study would delay or compromise care in any way.
2. Participants who are not able to understand or provide written consent.
reshma.rajan-joy@gehealthcare.com445-221-3076
yngvil.thomas@gehealthcare.com312-316-5632
mastroba@bcm.edu281-491-6830