BACKGROUND: Most people in the world lack access to medical imaging including for assessment of pulmonary disease. We sought to improve access to pulmonary imaging by developing a rapid automated system for triage of pulmonary disease using lung ultr...
OBJECTIVE: This study aims to explore the impact of different ROI delineation strategies on the axillary lymph nodes metastasis (ALNM) prediction model by analyzing two-dimensional ultrasound images of lymph nodes. In addition, we integrated clinical...
PURPOSE: To propose a multi-parametric ultrasound imaging-based deep learning method for accurately classifying metastatic and non-metastatic axillary lymph nodes in breast cancer patients.
Accurate differentiation between skull fractures and sutures is challenging in young children. Traditional diagnostic modalities like computed tomography involve ionizing radiation, while sonography is safer but demands expertise. This study explores...
OBJECTIVE: This study aimed to investigate the feasibility and potential value of predictive models for human epidermal growth factor receptor 2 (HER2)-positive status in breast cancer (BC) based on radiomics features from conventional ultrasound ima...
Accurate segmentation of gastric cavities from ultrasound images remains a challenging task due to the presence of ultrasound shadow and varying anatomical structures. To address these challenges, we collected a Gastric Ultrasound Image (GUSI) datase...
Insights into the general nature of motor skill could fundamentally change how we develop movement abilities, with implications for musculoskeletal well-being and injury. Here, we sought to identify indicators of general motor skill-those shared by e...
Lung ultrasound (LUS) vertical artifacts are critical sonographic markers commonly used in evaluating pulmonary conditions such as pulmonary edema, interstitial lung disease, pneumonia, and COVID-19. Accurate detection and localization of these artif...
INTRODUCTION: Difficult intubation is one of the most challenging scenarios to deal with due to increased morbidity and mortality. Machine learning systems can help predict this process in advance. This study aimed to predict whether patients had dif...
This study aimed to develop machine learning-based algorithms to assist physicians in ultrasound-guided localization of the cricoid cartilage (CC), thyroid cartilage (TC), and cricothyroid membrane (CTM) for cricothyroidotomy. Adult female participan...
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