This article is a correction to a review on the application of artificial intelligence (UI) in the diagnosis and management of fetal growth disorders. The review summarizes selected UI algorithms with potential in the diagnosis and management of abnormal fetal growth, including fetal growth restriction (FGR), small for gestational age (SGA), large for gestational age (LGA), and fetal macrosomia. The authors performed a comprehensive literature search of major databases to identify original and review articles on the use of UI in these disorders. Available evidence shows that UI models combining maternal, fetal and imaging data achieve accuracy comparable to experienced clinicians, increase operational efficiency and reduce variability. UI has the potential to enable earlier diagnosis, individualized monitoring and improved outcomes for mothers and newborns. Ethical, technical and regulatory challenges must be addressed for clinical use. The review emphasizes an integrative view of the full spectrum of fetal growth disorders to support precision perinatal medicine.[1][2]