Pregnancy

MRI-Only Simulation for Prostate MRI-Guided SBRT.

PURPOSE: The SMART (Stereotactic MR-Guided Adaptive Radiation Therapy) protocol for prostate SBRT has demonstrated favorable clinical outcomes using a 3T-MRI for delineation and a 0.35 T MR-Linac for adaptation, addressing challenges associated with low-field MRI delineation. However, this workflow necessitates three distinct simulation scans (CT, 3T-MRI, and 0.35T-MRI), resulting in logistical co...

Artificial Intelligence in Pharmaceutical Care: Transforming Drug Discovery, Development, and Patient-care Delivery.

The integration of artificial intelligence (AI) into pharmaceutical care represents a paradigm shift in healthcare delivery, offering unprecedented opportunities to revolutionize medication management, accelerate drug development, and enhance patient outcomes. This comprehensive review synthesized evidence from global literature (2021-2025) examining AI applications across drug discovery and devel...

Point-of-care ultrasound in cardiovascular imaging: current status and future prospects.

INTRODUCTION: As ultrasound technology has become more advanced and accessible over the years, point-of-care ultrasound (POCUS) is becoming a tool as ...

A Predictive Nomogram Integrating AI-Assisted Morphological Feature Extraction with Clinical and Ultrasound Parameters for Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

OBJECTIVE: To develop and validate a nomogram integrating artificial intelligence (AI)-extracted ultrasound features with clinic pathologic data for n...

A Systematic Review and Meta-analysis of Two-Dimensional Breast Ultrasound Radiomics: Implications for Lesion Characterization and Diagnostic Accuracy.

Radiomics applied to two-dimensional breast ultrasound has emerged as a potential noninvasive approach for differentiating benign from malignant breas...

Cross-Center Online Generalization Algorithm with Unadversarial Consistency for Fetal Heart Ultrasound View Recognition.

Fetal congenital heart disease (FCHD) remains a leading cause of infant mortality globally, yet the clinical deployment of deep learning models for au...

Pilot feasibility study of deep learning-based detection of malignant liver lesions in intraoperative ultrasound imaging.

BACKGROUND: Intraoperative ultrasound plays a central role in hepatobiliary surgery for the detection of liver lesions, but image interpretation is ch...

Deep learning-based automatic identification model of main pancreatic duct in intraoperative ultrasonography.

BACKGROUND: Pancreatic enucleation (PE) preserves parenchyma in benign/low-grade malignant pancreatic tumors but risks postoperative pancreatic fistul...

Construction and validation of a machine learning model for predicting early pregnancy in patients with polycystic ovary syndrome: a retrospective cohort study.

OBJECTIVE: Polycystic ovary syndrome (PCOS) is a leading cause of female infertility, and early pregnancy outcomes in affected women are affected by m...

Early detection of severe fetal growth restriction using multimodal deep learning based on ultrasound and prenatal biomarkers.

OBJECTIVE: To develop and evaluate a multimodal deep learning model that integrates first- and second-trimester ultrasound images with first-trimester...

Task-shifting to nonexperts using artificial intelligence-guided point-of-care ultrasound: a cohort study of patient selection, image quality, and learning curves.

AIMS: To define rates of diagnostic image acquisition, clinical drivers of image quality and the learning curve for artificial intelligence (AI)-guide...

LKCAU-Net: A Large Kernel Coordinated Attention U-Net for Breast Tumors Segmentation in Ultrasound Images.

Breast cancer remains a significant health concern for women worldwide. Ultrasound imaging is widely adopted for screening due to its non-invasive and...

Artificial Intelligence in Fascial Ultrasound: A Structured Narrative Review and Evidence Map From Segmentation to Translational Requirements.

Artificial intelligence is increasingly used in ultrasound imaging, but its role in fascial ultrasound remains unclear. This structured narrative revi...

Structured Large Language Model Workflows for Motivational Interviewing in Health Behavior Change: Proof-of-Concept Study.

BACKGROUND: Motivational interviewing (MI) is an effective approach for supporting health behaviorchange, but face-to-face delivery is resource-intens...

Multimodal artificial intelligence for predicting postoperative cesarean scar diverticulum risk.

OBJECTIVES: To develop an artificial intelligence (AI) model to predict cesarean scar diverticulum (CSD) risk following cesarean scar pregnancy (CSP) ...

Artificial intelligence for sexual, reproductive and maternal health in Latin America and the Caribbean: a scoping review.

BACKGROUND: Artificial intelligence (AI) holds considerable promise for strengthening sexual, reproductive and maternal health (SRMH) by enhancing dia...

Artificial intelligence and CRISPR-based approaches for targeted delivery of bacteriophages.

The rapid emergence of multidrug-resistant (MDR) bacteria has increased interest in bacteriophage therapy as a promising alternative to conventional a...

A Pulmonary Ultrasound Dataset for Tumor Segmentation and Classification.

Pulmonary tumor diagnosis with ultrasound is clinically valuable yet technically challenging. Although deep learning has shown promise in supporting s...

pH-sensitive gelatin-montmorillonite-cerium oxide nanocarriers for controlled quercetin delivery and machine learning release prediction.

In this study, a novel pH-responsive hybrid nanocarrier with a water-in-oil-in-water (W/O/W) emulsion structure was developed using gelatin (G) as a b...

Development and validation of machine learning-based model for macrosomia and spontaneous preterm birth: A retrospective cohort study.

OBJECTIVES: This study aimed to develop and externally validate machine learning-based models for predicting macrosomia and spontaneous preterm birth ...