An observational study in Congenital Anomalies, Neonatal Complications and Perinatal Outcomes, sponsored by FetalFirst Limited. Not yet recruiting. Open to participants aged 1 Year to 1 Year, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-07-14.
Sponsored by FetalFirst Limited · Observational
This study aims to develop advanced artificial intelligence (AI) models that predict neonatal risks and complications based on historical multimodal health data, including ultrasound and MRI scans. The objective is to empower clinicians and provide clear, compassionate support for families navigating complex prenatal diagnoses.
The FetalFirst study employs observational, retrospective analysis utilizing DenseNet121 neural networks. It analyzes de-identified retrospective data comprising ultrasound images, MRI scans, and clinical documentation from existing medical records. This research has received ethical approval from Wales Research Ethics Committee (REC ref: 25/WA/0168, IRAS ID: 358793). Outcomes from this study are expected to significantly enhance clinical intervention strategies, offering healthcare professionals robust tools for earlier detection and improved management of congenital anomalies and neonatal risks. Additionally, the insights gained will provide critical support to parents facing high-risk pregnancies, assisting them in making informed decisions.
781 studies on the registry are indexed under Congenital Abnormalities; 77 are open to participants now.
This study's planned enrollment of 50,000 is above the median of 250 across 257 observational studies indexed under Congenital Abnormalities.
Browse Congenital Abnormalities studies →This is the only study on the registry with FetalFirst Limited as lead sponsor.
Counted across the registry records on this site, refreshed daily.
The population includes retrospective, anonymized neonatal records obtained from clinical datasets, focusing on neonates previously diagnosed or assessed for congenital anomalies and neonatal risks.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
This cohort consists of retrospective, anonymized neonatal health records, including ultrasound, MRI scans, and clinical documentation from previous cases, used to develop predictive AI models.
Accuracy of AI Model Predictions for Neonatal Risk
Evaluate the accuracy of DenseNet121-based AI models in predicting neonatal risks and congenital anomalies, measured by sensitivity, specificity, and overall prediction accuracy.
Time frame: 12 Months
No study locations are listed for this record.
Plan to share: No — Individual participant data (IPD) will not be shared due to ethical and privacy considerations. All data is pseudonymised and governed strictly by the approved Data Sharing Agreement, which restricts external sharing to protect participant confidentiality and comply with UK GDPR.
Start is estimated for Jul 2025; primary completion for Jun 2026, 11 months later.
How these figures are worked out, and which studies are left out of them.
This study is not yet recruiting, as verified in Jul 2025. You cannot join it, but the record below documents what was studied.
Get an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.