Integrated artificial intelligence and omics for prediction and monitoring of pre-eclampsia

Pre-eclampsia is a difficult pregnancy condition that causes high blood pressure and can lead to health complications in both mother and newborn, resulting in a higher fatality rate. It presents with a wide range of symptoms and lacks specific indicators, as the contemporary diagnostic techniques, including proteinuria testing and blood pressure measurements, are not reliable. The current evolution in artificial intelligence (AI) technology tends to show a promising transformation of pre-eclampsia management. AI algorithms are applied to process larger sets of clinical, biochemical, and image data that facilitate timely medical interventions by bringing up the early-onset and severity of pre-eclampsia. By analyzing the red cell distribution width (blood test indicators for pre-eclampsia), it is recognized as a cost-effective way of detecting inflammation. The application of AI technology on non-invasive diagnostic (wearable) devices enables continuous monitoring with imaging techniques for the placenta and retina via cloud-based systems. These developments are not only applied for early detection of pre-eclampsia, but also assist decision making capabilities in both high- and low-resource environments. This article explains how the growing use of AI is changing the way that pre-eclampsia is understood and managed, with the aim of improving accuracy and offering more personalized care for pregnant women.