INTRODUCTION: Maternal mortality refers to a mother's death owing to complications arising from childbirth or pregnancy. This issue is a forefront public health challenge around the globe which is pronounced in low- and middle-income countries, parti...
BACKGROUND: Labor anesthesia is commonly used for pain relief during labor, but it can increase the risk of intrapartum fever. Currently, there are no reliable tools to predict which parturients might develop fever before labor anesthesia. The predic...
The capacity to forecast nonreassuring fetal heart (NFH) is essential for minimizing perinatal complications; therefore, this research aims to establish if a machine learning (ML) model can predict NFH. This was a retrospective analysis of informatio...
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Mar 4, 2025
OBJECTIVE: To investigate high-risk factors for gestational diabetes mellitus (GDM) in early pregnancy through an analysis of demographic and clinical data, and to develops a machine-learning-based prediction model to enhance early diagnosis and inte...
Women should be aware of prenancy related health issues. A user-friendly model is developed in which the patients can use as well as clinicians to determine the risks associated with foetal development inside the womb, birth weight, whose effects are...
To evaluate the clinical performance and safety of the ONIRY system for obstetric anal sphincter injuries (OASI) detection versus three-dimensional endoanal ultrasound (EAUS). A prospective, comparative, multicentre, international study. Poland, Czec...
BMC medical informatics and decision making
Mar 3, 2025
BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The...
OBJECTIVE: To determine whether readily available patient, ultrasound and treatment outcome data can be used to develop, validate and externally test two machine learning (ML) models for predicting the success of expectant and medical management of m...
BACKGROUND: Low birth weight (LBW) is a health condition that affects over 20 million gestational outcomes worldwide. The current literature indicates that machine learning models have the potential to assist healthcare professionals in predicting LB...
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