Pregnancy

Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.

Since the discovery of the life-saving hormone insulin in 1921 by Dr. Frederick Banting in 1921, there have been many critical discoveries and technical breakthroughs that have enabled people living with type 1 diabetes (T1D) to live longer, healthier lives. The development of insulin pumps, continuous glucose monitoring systems, and automated insulin delivery (AID) systems has enabled people livi...

Deep Learning Model for Real-Time Nuchal Translucency Assessment at Prenatal US.

Purpose To develop and evaluate an artificial intelligence-based model for real-time nuchal translucency (NT) plane identification and measurement in prenatal US assessments. Materials and Methods In this retrospective multicenter study conducted from January 2022 to October 2023, the Automated Identification and Measurement of NT (AIM-NT) model was developed and evaluated using internal and exter...

A Deep Learning Model Based on High-Frequency Ultrasound Images for Classification of Different Stages of Liver Fibrosis.

BACKGROUND AND AIMS: To develop a deep learning model based on high-frequency ultrasound images to classify different stages of liver fibrosis in chro...

Automatic Detection of B-Lines in Lung Ultrasound Based on the Evaluation of Multiple Characteristic Parameters Using Raw RF Data.

B-line artifacts in lung ultrasound, pivotal for diagnosing pulmonary conditions, warrant automated recognition to enhance diagnostic accuracy. In thi...

Comparison of externally validated interpretable machine-learning model with the United States Preventive Services Task Force approach to pre-eclampsia risk assessment.

Real-time brain tumor detection in intraoperative ultrasound: From model training to deployment in the operating room.

Intraoperative ultrasound (ioUS) is a valuable tool in brain tumor surgery due to its versatility, affordability, and seamless integration into the su...

Advances in viral vector-based delivery systems for gene therapy: a comprehensive review.

Gene therapy offers a revolutionary approach for treating genetic and acquired disorders by delivering therapeutic genes to target cells. Viral vector...

Prenatal exposure to criteria air pollution and traffic-related air toxics and risk of autism spectrum disorder: A population-based cohort study of California births (1990-2018).

BACKGROUND: Autism spectrum disorder (ASD) prevalence has risen steadily in California (CA) over several decades, with environmental factors like air ...

SegQC: a segmentation network-based framework for multi-metric segmentation quality control and segmentation error detection in volumetric medical images.

Quality control (QC) of structures segmentation in volumetric medical images is important for identifying segmentation errors in clinical practice and...

Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors.

PURPOSE: Noninvasive, accurate and novel approaches to predict patients who will achieve pathological complete response (pCR) after neoadjuvant chemot...

Extracellular vesicles as nature's nano carriers in cancer therapy: Insights toward preclinical studies and clinical applications.

Extracellular vesicles (EVs), which are secreted by various cell types, hold significant potential for cancer therapy. However, there are several chal...

GroundingDINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Models

Accurate and generalizable object segmentation in ultrasound imaging remains a significant challenge due to anatomical variability, diverse imaging ...

Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasound

Ultrasound (US) is widely accessible and radiation-free but has a steep learning curve due to its dynamic nature and non-standard imaging planes. Ad...

Diffusion Model-based Data Augmentation Method for Fetal Head Ultrasound Segmentation

Medical image data is less accessible than in other domains due to privacy and regulatory constraints. In addition, labeling requires costly, time-i...

Diffusion Model-based Data Augmentation Method for Fetal Head Ultrasound Segmentation

Medical image data is less accessible than in other domains due to privacy and regulatory constraints. In addition, labeling requires costly, time-i...

Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound

Congenital uterine anomalies (CUAs) can lead to infertility, miscarriage, preterm birth, and an increased risk of pregnancy complications. Compared ...

UltraTwin: Towards Cardiac Anatomical Twin Generation from Multi-view 2D Ultrasound

Echocardiography is routine for cardiac examination. However, 2D ultrasound (US) struggles with accurate metric calculation and direct observation o...

ChatGPT-4-Driven Liver Ultrasound Radiomics Analysis: Diagnostic Value and Drawbacks in a Comparative Study.

BACKGROUND: Artificial intelligence (AI) is transforming medical imaging, with large language models such as ChatGPT-4 emerging as potential tools for...

Federated Breast Cancer Detection Enhanced by Synthetic Ultrasound Image Augmentation

Federated learning (FL) has emerged as a promising paradigm for collaboratively training deep learning models across institutions without exchanging...

Hierarchical Corpus-View-Category Refinement for Carotid Plaque Risk Grading in Ultrasound

Accurate carotid plaque grading (CPG) is vital to assess the risk of cardiovascular and cerebrovascular diseases. Due to the small size and high int...