Research in developmental disabilities
Jun 18, 2025
INTRODUCTION: Pain assessment in individuals with cerebral palsy (CP), particularly those unable to self-report, is a significant challenge. Pain is the most common comorbidity in CP, yet current evaluation methods are often subjective and unreliable...
The simultaneous monitoring of both blood glucose level (BGL) and blood pressure (BP) has rarely been studied directly. The exploitation of physiological interactions between them will advance the learning of either task. However, the lack of availab...
Cardiovascular diseases remain a major cause of mortality and disability, underscoring the need for improved analysis of brain hemodynamics. The Circle of Willis plays a crucial role in maintaining cerebral blood flow; however, conventional measureme...
OBJECTIVES: To develop and validate a CT image-based multiple time-series deep learning model for the longitudinal prediction of benign and malignant pulmonary ground-glass nodules (GGNs).
PURPOSE: This study explores a multi-modal deep learning approach that integrates pre-intervention neuroimaging and clinical data to predict endovascular therapy (EVT) outcomes in acute ischemic stroke patients. To this end, consecutive stroke patien...
Few-shot learning alleviates the heavy dependence of medical image segmentation on large-scale labeled data, but it shows strong performance gaps when dealing with new tasks compared with traditional deep learning. Existing methods mainly learn the c...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 18, 2025
Popliteal sciatic nerve block is a widely used technique for lower limb anesthesia. However, despite ultrasound guidance, the complex anatomical structures of the popliteal fossa can present challenges, potentially leading to complications. To accura...
Peripheral Nerves (PNs) are traditionally evaluated using US or MRI, allowing radiologists to identify and classify them as normal or pathological based on imaging findings, symptoms, and electrophysiological tests. However, the anatomical complexity...
Diagnosing mitochondrial diseases remains challenging because of the heterogeneous symptoms. This study aims to use machine learning to predict mitochondrial diseases from phenotypes to reduce genetic testing costs. This study included patients who u...
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