Pregnancy

Concordant and discordant gene expression signatures of twin placentas in the setting of preeclampsia

Multifetal pregnancies are associated with increased risk for preeclampsia (PreE), but the underlying pathogenesis may differ from singleton gestations. It remains unclear whether both placentas in twin pregnancies complicated by PreE exhibit molecular signatures of the disease simultaneously or in isolation. We performed RNA sequencing on 32 individual placental samples from twin gestations group...

Automated Assessment of Choroidal Mass Dimensions Using Static and Dynamic Ultrasonographic Imaging

To develop and validate an artificial intelligence (AI)-based model that automatically measures choroidal mass dimensions on B□scan ophthalmic ultrasound still images and cine loops. Retrospective diagnostic accuracy study with internal and external validation. The dataset included 1,822 still images and 283 cine loops of choroidal masses for model development and testing. An additional 182 still ...

Miniaturized Four-Dimensional Functional Ultrasound for Mapping Human Brain Activity

Real-time brain monitoring for neurosurgery and neuroscience research of natural behaviors demands portable imaging with high spatiotemporal resolutio...

Automated biometry for assessing cephalopelvic disproportion in 3D 0.55T fetal MRI at term

Fetal MRI offers detailed three-dimensional visualisation of both fetal and maternal pelvic anatomy, allowing for assessment of the risk of cephalopel...

A Hybrid CNN-Transformer Deep Learning Model for Differentiating Benign and Malignant Breast Tumors Using Multi-View Ultrasound Images

Breast cancer is a leading malignancy threatening women’s health globally, making early and accurate diagnosis crucial. Ultrasound is a key screening ...

Diagnostic accuracy of Impedance Spectroscopy versus Digital Rectal Examination for Obstetric Anal Sphincter Injuries: a postpartum post-hoc analysis

Accurate diagnosis of obstetric anal sphincter injuries (OASIs) is critical for timely repair and prevention of long-term morbidity, yet digital recta...

Signal Mining and Analysis of Adverse Events of Isotretinoin: 20-year real-world pharmacovigilance analysis based on the FAERS database

To identify post-marketing adverse event (AE) signals associated with isotretinoin using real-world data from the U.S. Food and Drug Administration (F...

Deep Learning for Breast Mass Discrimination: Integration of B-Mode Ultrasound & Nakagami Imaging with Automatic Lesion Segmentation

This study aims to enhance breast cancer diagnosis by developing an automated deep learning framework for real-time, quantitative ultrasound imaging. ...

Machine learning and natural language processing for the early detection of potential mental disorders among school-age children: a prospective birth cohort study

Early detection of childhood mental health disorders remains challenging due to gaps in current screening approaches that lack sensitivity to subtle p...

Predictive Modelling’s role in Improving Pre-exposure Prophylaxis (PrEP) Uptake in High-Risk HIV Groups in Africa: An Integrative Scoping Review

This scoping review explores how predictive modelling can strengthen pre-exposure prophylaxis (PrEP) uptake among high-risk populations in Africa, whe...

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging

Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid...

Early Prediction of Gestational Diabetes Using Integrated Cell-free DNA Features and Omics-derived Genetic Scores

Gestational diabetes mellitus (GDM) affects 15.6% of pregnancies globally, with Vietnam exhibiting one of the highest prevalences at 21%. Current diag...

Large language models in radiologic numerical tasks: A thorough evaluation and error analysis

To investigate the performance of LLMs in radiology numerical tasks and perform a comprehensive error analysis. We defined six tasks: extracting 1-min...

Machine Learning for Dynamic and Short-term Prediction of Preeclampsia Using Routine Clinical and Laboratory Data

Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity and mortality, yet its unpredictable onset and rapid progression hinder timel...

Reinforcement learning optimization of automated insulin delivery in type 1 and type 2 diabetes mellitus

Closed-loop insulin delivery systems have proven effective in regulating blood glucose (BG) concentration, thereby reducing the burden of self-care in...

Performance of a Large Language Model in BI-RADS Classification of Ultrasound Based Breast Lesions

Given the advent of large language models (LLMs), the number of potential applications using artificial intelligence technologies in radiology has rap...

Systems Vaccinology Reveals Distinct Immune Signatures of Inhaled and Intramuscular SARS-CoV-2 Vaccination in Humans

Mucosal vaccines may reduce both infection and transmission by engaging local immunity, yet the immunological pathways they activate in humans remain ...

Breast Cancer Detection with Topological Deep Learning

In this paper, we investigate the integration of topological data analysis (TDA) techniques with deep learning (DL) models to improve breast cancer di...

Evaluating Conversational Image Segmentation for Medicine: Performance, Failure Modes, and a Fairness Audit Across Seven Modalities

Medical-image segmentation underpins quantitative diagnostics and research, yet state-of-the-art models remain task-specific and data-hungry. The rece...

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evaluation of artificial intelligence (AI)–assisted scr...