Pregnancy

Navigated hepatic tumor resection using intraoperative ultrasound imaging.

PURPOSE: This proof-of-concept study evaluates the feasibility and accuracy of an ultrasound-based navigation system for open liver surgery. Unlike most conventional systems that rely on registration to preoperative imaging, the proposed system provides navigation-guided resection using 3D models generated from intraoperative ultrasound. METHODS: A pilot study was conducted in 25 patients undergoi...

Normative growth trajectories of fetal brain regions validated by satisfactory maturation of neurodevelopmental domains at 2 years of age.

We previously constructed a qualitative, 3D ultrasound derived atlas of the normative spatiotemporal dynamics of fetal brain maturation. Here, using the same healthy multi-national cohort, we applied deep learning methods to 4205 fetal brain scans from 18-27 weeks' gestation, to produce an extensive, quantitative description of the growth of 16 fetal brain structures associated with satisfactory d...

Comparative machine learning models for early prediction of preterm birth from maternal serum biomarkers.

BACKGROUND: Preterm birth (PTB) is a major cause of neonatal morbidity and mortality. Inflammation and metabolic disruption are involved in its pathol...

The power of machine learning models in predicting gestational diabetes mellitus.

Features of B-mode ultrasound and contrast-enhanced ultrasound of carotid plaque based on deep learning enhance the prediction of vulnerable plaques associated with acute ischemic stroke.

OBJECTIVES: To develop an AI model using ultrasound features of carotid plaque for predicting the risk of acute ischemic stroke (AIS) and assess its e...

Distinction Between Benign and Borderline/Malignant Phyllodes Tumor in Breast Mammography and Ultrasound Based on Radiomics Methods.

RATIONALE AND OBJECTIVES: This study aims to evaluate whether radiomics methods used on breast mammography (MG) and ultrasound (US) could distinguish ...

Inflammatory indices, machine learning and artificial intelligence in tubal ectopic pregnancy management.

OBJECTIVE: To assess the predictive value of hematologic and biochemical inflammatory indices for methotrexate (MTX) treatment outcomes in tubal ectop...

Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.

Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such as nodular goiter and thyroid cancer (especially pa...

Identifying a better-prognosis pancreatic cancer from its benign inflammatory mimic: a machine learning approach with contrast-enhanced ultrasound for early intervention.

PURPOSE: Hypervascular pancreatic ductal adenocarcinoma (PDAC) and mass-forming pancreatitis (MFP) represent a classic diagnostic mimicry on contrast-...

Performance of Radiologist in Interpretation of Non-mass Lesions Detected by Automated Breast Ultrasound: With and Without Commercially Available AI.

OBJECTIVES: To evaluate the performance of radiologists with artificial intelligence (AI)-based computer-aided detection (CAD) systems on automated br...

Nanoengineering of Exosomal Surfaces for Precision Targeting and Payload Delivery at the Molecular Level.

Exosomes, nano-sized extracellular vesicles secreted by almost all cell types, have emerged as biologically compatible vehicles for targeted drug deli...

Deep Learning Integration of Endoscopic Ultrasound Features and Serum Data Reveals LTB4 as a Diagnostic and Therapeutic Target in ESCC.

BACKGROUND: Early diagnosis and accurate prediction of treatment response in esophageal squamous cell carcinoma (ESCC) remain major clinical challenge...

Dual-Parallel Artificial Intelligence Framework for Breast Cancer Grading via High-Intensity Ultrasound and Biomarkers.

BACKGROUND: Accurate and noninvasive breast cancer grading and therapy monitoring remain critical challenges in oncology. Traditional methods often re...

Artificial intelligence-driven nano-enhanced stem cell therapy for neurodegenerative diseases: from rational design to clinical translation.

Neurodegenerative diseases (NDs) are progressive and incurable central nervous system disorders characterized by the accumulation of pathological prot...

Automated Non-Invasive Burn Diagnostic System for Healthcare using Artificial Intelligence: AMBUSH-AI.

OBJECTIVE: Develop technology to predict burn wound depth using a combination of FDA approved ultrasound modalities and interpretation of these images...

Self-supervised ultrasound B-mode strain elastography using SMURF.

Displacement tracking is an integral part of ultrasound strain elastography (USE) and various approaches have been proposed over the last three decade...

Novel Lipid Nanoparticle (LNP) Delivery Systems Enabling the Advancement of RNA Therapeutics.

Lipid nanoparticle (LNP)-mRNA technology has profoundly transformed the biomedical landscape, establishing itself as a highly versatile and powerful p...

Intraoperative Ultrasound-Based Displacement Mapping Through Deep Learning.

BACKGROUND AND OBJECTIVES: Brain shift during neurological surgery for brain tumors can be caused by factors such as retraction, resection, and osmoti...

An ultrasound-based artificial intelligence framework for difficult airway prediction: A two-model, three-step decision framework.

BACKGROUND: At present, the early warning of difficult airway remains fraught with challenges. Previous ultrasonic quantitative parameters have demons...

OnUVS: An Online Motion Transfer Framework with Content-Texture Decoupling for High-Fidelity Ultrasound Video Synthesis.

Ultrasound (US) imaging plays a crucial role in diagnosing heart and pelvic diseases, where sonographers tend to evaluate dynamic motion and structure...