Pregnancy

Translating human capital amid varying intentions to stay: An integrative conceptual review of the immigrant employment attainment process.

Immigrants face a unique challenge in translating their home country human capital to secure employment in their host country's labor market, potentially leading to underemployment. In this integrative conceptual review, we formalize a framework to explain the process of human capital translation for immigrants, specifically laborers and professionals. Synthesizing findings across disciplines, we ...

A novel approach to preeclampsia early prediction addressing predictive uncertainty due to missing data in clinical dataset.

Preeclampsia (PE) is a disease that seriously threatens the health of pregnant women, and early intervention significantly reduce its incidence in high-risk mothers. To identify PE high-risk mother with a certain level of confidence or higher, we aimed to develop a framework for early prediction of preeclampsia (PE), which provides risk scores along with its associated uncertainty score due to mis...

Artificial intelligence and predictive analytics in obstetric anesthesia: early warning for maternal complications.

PURPOSE OF REVIEW: Maternal morbidity and mortality remain largely preventable, yet current risk-assessment tools identify only a fraction of women wh...

External validation of GDM risk prediction models using a machine learning reciprocal model-exchange framework.

BACKGROUND: Although many risk prediction models have been developed, very few undergo external validation, primarily due to issues with data access. ...

Noninvasive Staging of Hepatic Fibrosis in Patients with Autoimmune Liver Disease Using Deep Learning.

RATIONALE AND OBJECTIVES: Accurate staging of hepatic fibrosis is essential for guiding immunosuppressive and antifibrotic therapies. However, percuta...

DNA Methylation Markers for Pregnancy Hypertension via Machine Learning Methods.

BACKGROUND: This study aims to develop a prediction model to identify individuals at risk of hypertensive disorders of pregnancy (HDPs), including ges...

Dynamic ultrasound motion metrics combined with deep learning for clinical differentiation of subacromial impingement syndrome.

PURPOSE: This prospective study evaluated the diagnostic performance of deep learning models in predicting subacromial impingement syndrome (SIS) duri...

Training the diagnostic artificial intelligence in thyroid sonography: how well is deep learning truly learning?

INTRODUCTION: The use of artificial intelligence (AI) for TI-RADS classification in neck sonography for the assessment of thyroid nodules has been pro...

Heterogeneous graph neural networks reveal molecular mechanisms of folate deficiency in placental insufficiency through multiomics integration.

Placental insufficiency affects five to ten% of pregnancies worldwide, and folate deficiency has emerged as a key contributing factor. The molecular p...

Deep learning-based detection of retinal detachment with vitreous hemorrhage in ocular ultrasound images.

Retinal detachment (RD) is a serious ocular disease that can lead to permanent vision loss. In cases with fundus-obscuring vitreous hemorrhage (VH), i...

Quality-label-free fetal brain MRI quality control based on image orientation recognition uncertainty.

Quality control (QC) in fetal MRI is essential for efficient, high-quality data acquisition and analysis aimed at assessing fetal brain development an...

A Review on AI-Based Data-Driven Models for Optimization of Nanocarriers as Drug Delivery Systems.

Artificial intelligence (AI), primarily machine learning (ML), has revolutionized as a transformative strategy to accelerate nanomedicine research and...

Evaluation of KU-F40 automated microscope for parasitology: when artificial intelligence meets old school microscopy.

Intestinal parasitic infections (IPIs) have a worldwide distribution and have a major impact on health, work capacity, and economy in many countries. ...

HLA-DPA1 as a diagnostic biomarker differentiating early- and late-onset preeclampsia.

The occurrence and development of a wide range of preeclampsia (PE), especially early-onset preeclampsia (EOPE), is closely associated with the immune...

What's new in intravenous anaesthesia?

PURPOSE OF REVIEW: Advances in intravenous anaesthesia are driven by the need for agents with improved safety, enhanced hemodynamic stability, predict...

Prenatal alcohol exposure and the retrosplenial cortex: Structural and functional mechanisms across species.

The retrosplenial cortex (RSC) is a structurally and functionally complex hub with broad connectivity, integrating sensory inputs, cognitive states, a...

Development of a hybrid deep learning-based framework for liver fibrosis classification using ultrasound images.

BACKGROUND AND AIMS: Liver fibrosis is a progressive accumulation of extracellular matrix proteins with distortion of hepatic architecture and can pro...

Artificial Intelligence-based analysis of pre-eclampsia gene expression profiles for identification of novel potential pre-eclampsia diagnostic biomarkers.

Preeclampsia (PE) is a multifactorial and heterogeneous hypertensive disorder of pregnancy that poses significant diagnostic and therapeutic challenge...

Current and future use of artificial intelligence in valvular heart disease imaging.

Valvular heart disease (VHD) remains significantly underdiagnosed and undertreated. This review examines an artificial intelligence (AI)-enhanced 'spo...

Redefining Tumor Vascular Permeability through Deep Learning-Guided Microneedle Delivery.

Low-permeability (LP) tumor vasculature constitutes a major barrier to efficient nanomedicine delivery, making quantitative assessment and mechanistic...