Latest AI and machine learning research in pregnancy for healthcare professionals.
OBJECTIVE: The impact of chronic hypertension (CHTN) combined with left ventricular hypertrophy (LVH) on adverse maternal and fetal pregnancy outcomes remains unclear. METHODS: This multicenter retrospective cohort study included pregnant women with CHTN from four tertiary hospitals in China. Baseline characteristics were compared using the Kruskal-Wallis and Chi-squared tests with Bonferroni corr...
PURPOSE: The increasing incidence of lower gastrointestinal neuroendocrine tumors (NETs) necessitates improved methods for early and accurate detection. Automatic segmentation of NETs in endoscopic ultrasound (EUS) images is particularly challenging due to low image contrast and indistinct tumor boundaries. This study proposes and validates GismEUS, a geometry-aware deep learning model for automat...
Gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), preterm birth, and intrauterine growth restriction represent major con...
BACKGROUND: Multimodal large language models (LLMs) are increasingly being explored for medical image analysis, but their relative performance in thyr...
INTRODUCTION: Central venous cannulation is essential for life-saving interventions including resuscitation of critically ill patients, hemodynamic mo...
The laminar nature of blood flow and the resulting boundary layer pose substantial challenges for transverse mass transport in blood vessels, limiting...
Effects of stroke therapies area highly time dependent but onset-to-treatment times for recanalizing treatment are mostly beyond optimal time windows....
OBJECTIVES: To compare the diagnostic performance of three multimodal AI chatbots on oral and maxillofacial radiographic images and to examine how add...
BACKGROUND: The development of deep learning techniques has greatly improved tumor detection and analysis in breast ultrasound images. Despite their i...
Artificial intelligence (AI) is increasingly embedded in healthcare delivery, yet its evaluation remains dominated by technical performance metrics th...
Oral drug delivery is preferred for patient compliance, but it's challenging for biologics and sensitive therapeutics due to the harsh gastrointestina...
The objective of the study is to develop and externally evaluate interpretable machine learning models integrating routinely reported ultrasound and M...
BACKGROUND: Sleep supports neurophysiological maturation in preterm infants, yet the impact of developmental care interventions on sleep remains poorl...
Nucleic acid therapeutics offer promise for precision cancer treatment, but are limited by inaccurate target selection and inefficient delivery. This ...
The relative use of shock wave lithotripsy (SWL) has declined with the expansion of endourological techniques, although SWL remains widely available. ...
OBJECTIVE: Adiposity rebound (AR), the second rise in BMI during growth, increases the risk of obesity and metabolic diseases when it occurs early. We...
Aging is a significant risk factor of neurodegenerative disorders (NDs) such as Huntington's, Alzheimer's, Parkinson's, amyotrophic lateral sclerosis ...
Ultrasound imaging is widely used across cardiology, hepatology, obstetrics, breast and thyroid imaging, and emergency care because it is real-time, n...
SASH1 is a signal adaptor protein involved in cell growth, apoptosis, and immune regulation, and has been increasingly studied in tumor and immune cel...
Nanoparticle (NP)-based drug delivery systems hold great promise for cancer treatment. However, designing efficient NP formulations for clinical usage...