Pregnancy

Automated subcutaneous fat segmentation with a convolutional neural network in magnetic resonance guided high-intensity focused ultrasound treatment for uterine fibroids.

INTRODUCTION: In MR-guided high-intensity focused ultrasound (MR-HIFU) treatment for uterine fibroids, the subcutaneous abdominal fat layer is prone to unwanted heating, especially during consecutive sonications. Automating its delineation with a deep learning algorithm would enhance treatment safety, efficiency and simplify clinical workflow. MATERIALS AND METHODS: The subcutaneous fat layer was ...

Harnessing Hitchhikers: Outer Membrane Vesicles Leading the Way in Advanced Cancer Therapeutics and Diagnostic- A Review.

Cancer therapy is increasingly shaped by delivery platforms designed to overcome the limitations of conventional chemotherapy and radiotherapy. Among these, bacterial outer membrane vesicles (OMVs) have emerged as versatile nanocarriers with intrinsic tumor-interacting properties, immunomodulatory capacity, and amenability to bioengineering. Their lipid bilayer composition not only enhances stabil...

Synergizing Artificial Intelligence with In Vivo CAR-T Cell Generation: A New Paradigm for Democratized Immunotherapy.

In vivo CAR-T cell generation represents a paradigm shift in immunotherapy by transitioning the production of chimeric antigen receptor (CAR) T cells ...

Artificial intelligence for personalized multiple micronutrient supplementation in maternal health.

Maternal undernutrition and micronutrient deficiencies remain pervasive, contributing to adverse pregnancy outcomes and long-term health risks for mot...

Beyond Human Variability: Deep Learning for Intravascular Ultrasound Segmentation With Noisy Labels.

OBJECTIVE: Intravascular ultrasound (IVUS) is an imaging modality that provides cross-sectional visualization of the coronary lumen and vessels. To ad...

Integrating aqli (rationale) and naqli (revealed) knowledge in AI-driven clinical decision support systems to enhance healthcare delivery for guiding termination of pregnancy among Muslim patients: a systematic review (1).

Clinical utility assessment framework for machine learning-based fetal health classification in cardiotocography: an observational study.

OBJECTIVE: To evaluate the clinical utility and implementation considerations of artificial intelligence (AI)-based fetal health classification system...

Evaluation of Generative Artificial Intelligence Safeguards Against the Creation of Images and Videos Harmful to Public Health.

OBJECTIVES: As generative artificial intelligence (AI) continues to advance, an environment that lacks strong safeguards could create opportunities fo...

Endoscopic Ultrasound for the Management of Pancreatic Neuroendocrine Tumors: Diagnosis, Treatment, and Future Perspectives.

Pancreatic neuroendocrine tumors (PanNETs) are increasingly diagnosed, reflecting greater clinical awareness, improved imaging, and revised classifica...

Diagnostic Imaging Pathways in Peripheral Artery Disease: A Comparative Review of Duplex Ultrasound Through Computed Tomography Angiography.

Peripheral artery disease (PAD) is a major global health challenge, affecting more than 200 million people worldwide and an estimated 8 to 12 million ...

AURA-CVC: Autonomous Ultrasound-guided Robotic Assistance for Central Venous Catheterization.

PURPOSE: Central venous catheterization (CVC) is a critical medical procedure for vascular access, hemodynamic monitoring, and life-saving interventio...

GlucoseGo: a simple tool to predict hypoglycaemia during exercise in type 1 diabetes.

AIMS/HYPOTHESIS: This study aimed to develop an accessible tool, derived using machine learning, to predict hypoglycaemia risk at the start of exercis...

Ultrasound-Responsive Serotonylation and Hallmark Pathway Gene Signatures Reveal Tumor Microenvironment Vulnerabilities and Prognostic Subtypes in Colorectal Cancer.

BACKGROUND: Focused ultrasound, low-intensity focused ultrasound, and microbubble-enhanced sonoporation are examples of ultrasound-based cancer therap...

Targeting metabolic vulnerabilities with advanced delivery systems.

Metabolism modulation has emerged as a promising frontier in precision oncology. Nonetheless, the primary gap is the inability to precisely target the...

LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA delivery.

Integrating AI with robotics offers a promising approach to molecular discovery and optimization, enabling efficient exploration of vast chemical spac...

Machine learning-based endometrial ultrasound radiomics habitat analysis for predicting pregnancy outcomes after embryo transfer.

Enhancing agreement in cardiotocography interpretation between midwives and obstetricians through a rule-based AI program: A comparative cross-sectional study.

OBJECTIVE: To evaluate whether a rule-based artificial intelligence (AI) program can enhance interrater agreement in cardiotocography (CTG) interpreta...

Agentic AI and the rise of in silico team science in biomedical research.

Agentic artificial intelligence (AI) systems are emerging as teams of intelligent computational experts capable of rivaling human performance in labor...

Advancements of ultrasound modalities and their clinical potential in ophthalmology.

Ultrasound imaging has played an important role in ophthalmic diagnostics due to its real-time capability, safety, and cost-effectiveness. In recent y...

Integrating B-mode ultrasound radiomics and clinical variables to predict 26-week progression-free survival in advanced hepatocellular carcinoma under targeted immunotherapy.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality globally, with over 905,700 new cases and 830,200 de...