The Role of Artificial Intelligence from Preconception to Postpartum

Abstract

Artificial intelligence (AI) is increasingly applied across obstetrics, supporting care from preconception to postpartum. By using large databases, including imaging, genomics, laboratory profiles, and electronic health records, machine learning and deep learning models can generate insights that surpass traditional methods, and enable more personalized maternal–fetal care. In the preconception and fertility stage, AI is a tool used in infertility diagnostics, sperm, oocyte and embryo selection in assisted reproductive technology, improving success rates and efficiency. During pregnancy predictive algorithms can help with monitoring fetal biometry and fetal growth rate.  AI also contributes to intrapartum monitoring by providing more consistent interpretation of cardiotocography and contraction patterns, potentially reducing unnecessary interventions and improving neonatal outcomes. Similarly to ultrasound during pregnancy AI can be used to analyze intrapartum ultrasound monitoring and help in diagnosing dystocia which could lead to fewer cesarian sections and further complications. Intrapartum and during early postpartum period AI can be used to evaluate and predict possible postpartum hemorrhage.  Despite significant progress, challenges remain regarding data quality, algorithmic bias, interpretability, and integration into everyday practice. However, with further research and use in everyday clinical practice AI has a possibility to become an irreplaceable tool to every practitioner.