Background Research on the integration of artificial intelligence (AI) into community-based
primary health care (CBPHC) has highlighted several advantages and disadvantages in …

Background Machine learning (ML) is increasingly being used in many areas of health care.
Its use in infection management is catching up as identified in a recent review in this journal …

OBJECTIVE: To develop and validate an expanded obstetric comorbidity score for predicting
severe maternal morbidity that can be applied consistently across contemporary US patient …

OBJECTIVE: To predict a woman's risk of postpartum hemorrhage at labor admission using
machine learning and statistical models. METHODS: Predictive models were constructed …

Background The applications of artificial intelligence (AI) processes have grown significantly
in all medical disciplines during the last decades. Two main types of AI have been applied in …

This study reviews recent advances on the application of artificial intelligence for the early
diagnosis of various maternal-fetal conditions such as preterm birth and abnormal fetal …

Health information technology (health IT) potentially is a promising vital lever to address
racial and ethnic, socioeconomic, and geographic disparities in maternal morbidity and …

Artificial Intelligence has been widely applied to a majority of research areas, including
health and medicine. Certain complications or disorders that can appear during pregnancy …

Maternal health refers to the physical, mental, and emotional well-being of mothers
throughout all stages of pregnancy, birth, and the postpartum period. Morbidity and death …

Purpose This work used a machine learning model to improve the accuracy of predicting
postpartum hemorrhage in vaginal delivery. Methods Among the 25,098 deliveries in the …