Pregnancy

Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data.

Synthetic and naturally occurring particles, such as nanoparticles (NPs) and exosomes; a type of ext...

Corrigendum to "Ultrasound-Based Deep Learning Radiomics Nomogram for Tumor and Axillary Lymph Node Status Prediction After Neoadjuvant Chemotherapy" [Academic Radiology 32 (2025) 12-23].

An Ultrasound Image-Based Deep Learning Radiomics Nomogram for Differentiating Between Benign and Malignant Indeterminate Cytology (Bethesda III) Thyroid Nodules: A Retrospective Study.

RATIONALE AND OBJECTIVES: Our objective is to develop and validate a deep learning radiomics nomogra...

Machine learning-based fusion model for predicting HER2 expression in breast cancer by Sonazoid-enhanced ultrasound: a multicenter study.

PURPOSE: To predict human epidermal growth factor receptor 2 (HER2) expression in breast cancer (BC)...

Res-ECA-UNet++: an automatic segmentation model for ovarian tumor ultrasound images based on residual networks and channel attention mechanism.

OBJECTIVE: Ultrasound imaging has emerged as the preferred imaging modality for ovarian tumor screen...

AI-driven healthcare: Fairness in AI healthcare: A survey.

Artificial intelligence (AI) is rapidly advancing in healthcare, enhancing the efficiency and effect...

Role of VATS-US in identifying and characterizing pulmonary nodules: a narrative review.

The aim of this study was to show the efficacy described in the scientific literature of lung ultras...

Circadian Rhythm of Heart Rate and Heart Rate Variability in Pregnancy.

The autonomic nervous system (ANS) regulates physiological changes during pregnancy, supporting feta...

Development and validation of ultrasound-based radiomics deep learning model to identify bone erosion in rheumatoid arthritis.

OBJECTIVE: To develop and validate a deep learning radiomics fusion model (DLR) based on ultrasound ...

Semiautomated segmentation of breast tumor on automatic breast ultrasound image using a large-scale model with customized modules.

To verify the capability of the Segment Anything Model for medical images in 3D (SAM-Med3D), tailore...

DeTox: an Alternative to Animal Testing for Predicting Developmental Toxicity Potential.

BACKGROUND: Medication use among pregnant women is common, yet the safety of these medications for t...

Artificial Intelligence in Dermatology: A Comprehensive Review of Approved Applications, Clinical Implementation, and Future Directions.

This comprehensive review examines artificial intelligence (AI) applications in dermatology, approve...

Sex-Based Differences in Prenatal and Perinatal Predictors of Autism Spectrum Disorder Using Machine Learning With National Health Data.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder influenced by genetic, epige...

Transformer model based on Sonazoid contrast-enhanced ultrasound for microvascular invasion prediction in hepatocellular carcinoma.

BACKGROUND: Microvascular invasion (MVI) is strongly associated with the prognosis of patients with ...

Machine Learning for Predicting the Transition From Gestational Diabetes to Type 2 Diabetes: A Systematic Review.

Gestational diabetes mellitus (GDM) significantly increases the risk of developing type 2 diabetes (...

The association between maternal exposure to ten neonicotinoid insecticides and preterm birth in Guangxi, China.

Preterm birth (PTB) is a primary cause of mortality among newborns globally. Prenatal exposure to en...

Fair ultrasound diagnosis via adversarial protected attribute aware perturbations on latent embeddings.

Deep learning techniques have significantly enhanced the convenience and precision of ultrasound ima...

Optimization of Protein Extraction from Rapeseed Oil Cake by Dephenolization Process for Scale-Up Application Using Artificial Neural Networks.

Rapeseed proteins, due to their quality and wide availability, have great potential for application ...

Improved Prediction Accuracy for Late-Onset Preeclampsia Using cfRNA Profiles: A Comparative Study of Marker Selection Strategies.

: Late-onset pre-eclampsia (LO-PE) remains difficult to predict because placental angiogenic markers...

Deep learning predicts HER2 status in invasive breast cancer from multimodal ultrasound and MRI.

The preoperative human epidermal growth factor receptor type 2 (HER2) status of breast cancer is typ...

Modifying the U-Net's Encoder-Decoder Architecture for Segmentation of Tumors in Breast Ultrasound Images.

Segmentation is one of the most significant steps in image processing. Segmenting an image is a tech...