Artificial intelligence in cardio-obstetrics: Current applications and future perspectives

Cardiovascular disease (CVD) has become one of the leading causes of pregnancy related morbidity and mortality worldwide, reflecting a substantial epidemiological shift driven by increasing maternal age, obesity, diabetes, chronic hypertension, congenital heart disease survival into reproductive years, and other cardiovascular risk factors. These changing demographics have fueled the rapid evolution of cardio-obstetrics as a multidisciplinary subspecialty dedicated to optimizing maternal and fetal cardiovascular outcomes. Simultaneously, artificial intelligence (AI) has transformed modern healthcare by enabling data-driven prediction, automated image interpretation, precision risk stratification, and clinical decision support across multiple specialties. Although AI applications have expanded considerably within cardiology and obstetrics individually, their integration into cardio-obstetrics remains an emerging but highly promising field. This review examines the current landscape of AI in cardio-obstetric practice, emphasizing its role across the continuum of maternal cardiovascular care. Applications include machine learning based maternal cardiovascular risk prediction, automated interpretation of electrocardiography and echocardiography, deep learning for fetal cardiac imaging, electronic health record based predictive analytics, wearable physiological monitoring, telemedicine, and AI-assisted clinical decision support systems. Emerging technologies such as multimodal AI, explainable AI, federated learning, digital twins, and large language models are also explored for their potential to redefine individualized maternal cardiovascular care.