Artificial Intelligence Advancements in Fetal Monitoring: Enhancing Prenatal Care

Pregnancy and the delivery of a healthy baby rank among the crucial milestones in the human life cycle. Obstetrical science is devoted to ensuring these events unfold as smoothly as possible, promoting the well-being of both the infant and the mother. The primary challenge in achieving this objective is the occurrence of fetal deaths within the uterus, which represents a significant obstacle to the overall goal of a healthy outcome for the baby and the mother. Fetal monitoring is an essential aspect of prenatal care, aiming to assess the health and well-being of the developing fetus during pregnancy. There are various approaches for fetal monitoring used in clinical practice: cardiotocography (CTG) and Doppler ultrasound, fetal electrocardiography, fetal ecography etc. However there are crucial limitations: inter- and intra-observer variability, invasivity, low signal to noise ratio (SNR) etc. The aim of the present study is to evaluate the current contribution of artificial intelligence (AI) advancements in offering innovative solutions to enhance accuracy, early detection, and overall efficiency in assessing fetal health.