The American journal of emergency medicine
Jun 1, 2025
BACKGROUND: Triage is essential in emergency departments (EDs) to prioritize patient care based on clinical urgency. Recent investigations have explored the role of large language models (LLMs) in triage, but their effectiveness compared to human tri...
OBJECTIVES: To develop a deep learning (DL) model based on ultrasound (US) images of lymph nodes for predicting cervical lymph node metastasis (CLNM) in postoperative patients with differentiated thyroid carcinoma (DTC).
IEEE journal of biomedical and health informatics
Jun 1, 2025
Characterizing age-related alterations in brain networks is crucial for understanding aging trajectories and identifying deviations indicative of neurodegenerative disorders, such as Alzheimer's disease. In this study, we developed a Fully Hyperbolic...
IEEE journal of biomedical and health informatics
Jun 1, 2025
Fast virtual stenting (FVS) is a promising preoperative planning aid for thoracic endovascular aortic repair (TEVAR) of aortic dissection. It aims at digitally predicting the reshaped aortic true lumen (TL) under specific operation plans (stent-graft...
PURPOSE: Predicting long-term anatomical responses in neovascular age-related macular degeneration patients is critical for patient-specific management. This study validates a generative deep learning model to predict 12-month posttreatment optical c...
BACKGROUND AND AIMS: Insufficient bowel preparation accounts for up to 42% of missed adenomas in colonoscopy. However, major analysis programs found no correlation between adenoma detection rate and the human-rated Boston Bowel Preparation Scale (BBP...
In this article, I propose an ethical analysis of assistive domestic robots for older users. In doing so, I illustrate my inquiry with the example of ROB-IN assistive robot. ROB-IN is a Spanish project which is devoted to developing a robot that will...
PURPOSE: To establish a reliable machine learning model to predict malignancy in breast lesions identified by ultrasound (US) and optimize the negative predictive value to minimize unnecessary biopsies.
BACKGROUND: Machine learning (ML) models in healthcare are crucial for predicting clinical outcomes, and their effectiveness can be significantly enhanced through improvements in accuracy, generalisability, and interpretability. To achieve widespread...
BACKGROUND: Magnetic resonance imaging (MRI), combined with artificial intelligence techniques, has improved our understanding of brain structural change and enabled the estimation of brain age. Neurodegenerative disorders, such as Alzheimer's diseas...
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