AI is poised to make a substantial impact in maternal health by enhancing the prediction and management of complications during pregnancy. Recent studies, such as those conducted by Kaiser Permanente and Massachusetts General Hospital, have successfully used machine learning algorithms to predict obstetric complications by analyzing patterns in electronic health records (EHRs). This predictive capability can be a game-changer in preemptively addressing potential risks.

For instance, Stanford University School of Medicine's pilot program at Lucile Packard Children’s Hospital utilized AI to monitor vital signs and predict health risks, ensuring timely interventions for conditions like hemorrhaging, which is a leading cause of maternal death

Future Directions and the Need for Inclusive Technology

While the potential of AI and big data in improving maternal and neonatal health is clear, the deployment of these technologies must be inclusive. Addressing the digital divide and ensuring that women from all socioeconomic backgrounds have equal access to these technologies is crucial. Partnerships between tech companies, governments, and healthcare providers are essential to develop and fund AI solutions that are accessible to all, especially in under-resourced communities.