BACKGROUND: In the era of rapid digital transformation, it is crucial to cultivate research competence among nursing postgraduates to support innovation in nursing science and strengthen the overall competitiveness of the profession. However, limited... read more
Accurate prediction of pediatric epidemic infectious diseases is critical for effective prevention and personalized treatment. Herein, we developed a deep learning framework for the epidemiological characteristics of the Chaoshan region, using electr... read more
OBJECTIVE: To develop and validate a deep learning-based method for automated quantification of retinal ganglion cell axons in transmission electron microscopy (TEM) images, addressing the time-consuming and subjective nature of manual segmentation a... read more
BACKGROUND: Gait deviations are common in youth with Cerebral Palsy (CP), with the change in gait pattern during growth/development being influenced by a variety of individual and treatment factors. The goal of this study is to use Machine Learning (... read more
Indian journal of thoracic and cardiovascular surgery
Mar 3, 2026
PURPOSE: In India, myocardial infarction (MI) is a significant cause of mortality related to cardiovascular diseases. Timely diagnosis is critical for addressing this issue. While prior studies have concentrated on digital electrocardiogram (ECG) dat... read more
Gastrointestinal endoscopy clinics of North America
Mar 3, 2026
As artificial intelligence (AI) becomes integrated into gastrointestinal endoscopy, training programs must adapt to prepare learners for AI-assisted practice. This review outlines current AI applications, ranging from polyp detection to workflow anal... read more
Structural heart : the journal of the Heart Team
Mar 2, 2026
Accurate quantification of mitral regurgitation (MR) is essential for preprocedural evaluation and intraprocedural decision-making during transcatheter mitral interventions. Conventional echocardiographic techniques, such as the proximal isovelocity ... read more
Multispectral demosaicing is crucial to reconstruct full-resolution spectral images from snapshot mosaiced measurements, enabling real-time imaging from neurosurgery to autonomous driving. Classical methods are blurry, while supervised learning requi... read more
Precise spatial fidelity in Image-to-3D multi-instance generation is critical for downstream real-world applications. Recent work attempts to address this by fine-tuning pre-trained Image-to-3D (I23D) models on multi-instance datasets, which incurs s... read more
Atmospheric turbulence significantly degrades long-range imaging by introducing geometric warping and exposure-time-dependent blur, which adversely affects both visual quality and the performance of high-level vision tasks. Existing methods for synth... read more
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