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AI-Powered CURAᵀᴹ Application for Identifying At-Risk Pregnancies in Obstetric Management

National University Hospital, Singapore · 2025
ClinicalTrials.gov · Datasets · License: Public Domain · 2025
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artificial-intelligencemachine-learningpregnancypregnancy-complications
It is important to identify high pregnancies early through screening so that appropriate care and intervention may be instituted. An AI-assisted risk categorisation approach may be advantageous compared with traditional means of screening. The purpose of this study is to determine if the adoption of an AI-assisted approach in general pregnancy risk screening will improve the accuracy of antenatal risk categorization into high- and low- risk pregnancy groups, ultimately resulting in fewer poor maternal and fetal/neonatal outcomes.
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