Latest AI and machine learning research in pregnancy for healthcare professionals.
Transvaginal ultrasound is a critical imaging modality for evaluating cervical anatomy and detecting physiological changes. However, accurate segmentation of cervical structures remains challenging due to low contrast, shadow artifacts, and indistinct boundaries. While convolutional neural networks (CNNs) have demonstrated efficacy in medical image segmentation, their reliance on large-scale ann...
Frequent and long-term exposure to hyperglycemia (i.e., high blood glucose) increases the risk of chronic complications such as neuropathy, nephropathy, and cardiovascular disease. Current technologies like continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) primarily model specific aspects of glycemic control-like hypoglycemia prediction or insulin delivery. ...
This paper explores how artificial intelligence (AI) and robotics are transforming the global labor market. Human workers, limited to a 33% duty cyc...
Unmanned aerial vehicles (UAVs), initially developed for military applications, are now used in various fields. As UAVs become more common across mu...
Data augmentation is a central component of joint embedding self-supervised learning (SSL). Approaches that work for natural images may not always b...
This study presents a vision-guided robotic control system for automated fruit tree pruning applications. Traditional agricultural practices rely on...
Cognitive demands of fetal ultrasound examinations pose unique challenges among clinicians. With the goal of providing an assistive tool, we develop...
Accurate standard plane acquisition in fetal ultrasound (US) videos is crucial for fetal growth assessment, anomaly detection, and adherence to clin...
Monitoring maternal and fetal health during pregnancy is crucial for preventing adverse outcomes. While tests such as ultrasound scans offer high ac...
Integration of artificial intelligence (AI) in health and healthcare, especially for older adults, has significantly advanced healthcare delivery. AI ...
BACKGROUND: Severe esophagogastric varices (EGVs) significantly affect prognosis of patients with hepatitis B because of the risk of life-threatening ...
BACKGROUND AND AIM: Intestinal ultrasound (IUS) potentially spares patients from repeated endoscopies under sedation and eliminates the need for alter...
Ultrasound is a widely accessible and cost-effective medical imaging tool commonly used for prenatal evaluation of the fetal brain. However, it has ...
LLMs increasingly serve as tools for knowledge acquisition, yet users cannot effectively specify how they want information presented. When users req...
OBJECTIVES: This study aimed to investigate the value of a deep learning (DL) model based on greyscale ultrasound (US) images for precise assessment a...
This integrative literature review examines the evolving role of artificial intelligence (AI) and machine learning (ML) based clinical decision suppor...
Although most physicians are interested in the use of augmented or artificial intelligence (AI) in health care, only 38% are using AI in their practic...
We propose a novel approach that adapts hierarchical vision foundation models for real-time ultrasound image segmentation. Existing ultrasound segme...
Advances in deep learning have significantly enhanced medical image analysis, yet the availability of large-scale medical datasets remains constrain...
Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and ...