AI-Integrated Maternal Preeclampsia Detection and Care Transformation (AIMPact)

Obed Brew of Kwame Nkrumah University of Science and Technology in Ghana will explore applying a combination of AI-based analytical approaches to clinical data for early detection of preeclampsia in pregnancy to reduce maternal and neonatal morbidity and mortality. They will collect a diverse set of data from pregnant women, including physiological data from wearable devices, electronic health records, clinical notes, and fetal nucleic acids from non-invasive prenatal testing. They will apply a variety of AI tools to detect patterns across the data, such as associations between fetal gene signatures and maternal physiological markers. While evaluating the performance of the AI models in detecting preeclampsia, they will develop training programs for healthcare professionals in the use of AI tools in clinical settings.