Temporal echocardiography image registration is important for cardiac motion estimation, myocardial strain assessments, and stroke volume quantifications. Deep learning image registration (DLIR) is a promising way to achieve consistent and accurate r...
Systems biology in reproductive medicine
Jan 28, 2025
Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this s...
Diabetes mellitus (DM) represents a major global health challenge, affecting a diverse range of demographic populations across all age groups. It has particular implications for women during pregnancy and the postpartum period. The contemporary preva...
A new form of stethoscope with artificial intelligence (AI) capabilities may make the difference between early detection of pregnancy-induced cardiomyopathy or end stage postpartum heart failure. The AI stethoscope is a tool that may make that differ...
BACKGROUND: Birth-related mortality is significantly increased by home births without skilled medical assistance during delivery, presenting a major risk to the public's health. The objective of this study is to predict home delivery and identify the...
American journal of obstetrics & gynecology MFM
Jan 23, 2025
OBJECTIVE: Machine learning (ML), a subtype of artificial intelligence (AI), presents predictive modeling and dynamic diagnostic tools to facilitate early interventions and improve decision-making. Considering the global challenges of maternal, fetal...
Accurate measurement of frontomaxillary facial (FMF) angles in prenatal ultrasound (US) scans plays a pivotal role in the screening of trisomy 21. Nevertheless, this intricate procedure heavily relies on the proficiency of the ultrasonographer and te...
BACKGROUND: Antenatal depression (AND), occurring during pregnancy, is associated with severe outcomes. However, there is a lack of objective and universally applicable prediction methods for AND in clinical practice. We leveraged sociodemographic an...
BACKGROUND: Postpartum depression (PPD) is a prevalent mental health issue with significant impacts on mothers and families. Exploring reliable predictors is crucial for the early and accurate prediction of PPD, which remains challenging.
OBJECTIVE: The incidence of caesarean sections (CSs) has increased significantly in recent years, especially in developed countries. This study aimed to identify the factors that most influence the length of hospital stay (LOS) after a CS, using data...