This paper presents a novel system for optimizing Tai Chi movement training using computer vision and deep learning technologies. We developed a comprehensive framework incorporating multi-view pose estimation, temporal feature extraction, and real-t...
Digital twin (DT) technology is revolutionizing healthcare systems by leveraging real-time data integration and advanced analytics to enhance patient care, optimize clinical operations, and facilitate simulation. This study aimed to identify key rese...
It is well known that machine learning models require a high amount of annotated data to obtain optimal performance. Labelling Computed Tomography (CT) data can be a particularly challenging task due to its volumetric nature and often missing and/or ...
Telementoring in surgical training enables expert surgeons to provide real-time remote guidance to trainees. This technique is increasingly adopted to address surgical training gaps in low- and middle-income countries (LMICs), i.e., nations with a gr...
The purpose of this pilot study was to test an adapted childhood obesity prevention intervention called Preventing Obesity Using Digital-Assisted Movement and Eating (ProudMe) in under-resourced schools. Six schools were cluster-randomized to ProudMe...
The precise detection and localization of abnormalities in radiological images are very crucial for clinical diagnosis and treatment planning. To build reliable models, large and annotated datasets are required that contain disease labels and abnorma...
This study assessed ChatGPT's adherence to established management guidelines for status epilepticus (SE) from major neurological societies (NCS, AES, EFNS) and examined how prompt specificity affected the quality of its recommendations. Four prompts ...
The speech recognition task of the HaiNan dialect faces significant differences in phonology, intonation, and grammatical structure among dialects, which in turn show significant regionalization characteristics, which makes the task of dialect-to-Man...
We develop an evolutionary model for individual discriminatory behavior that emerges naturally in a mixed population as an adaptive strategy. Our findings show that, when individuals have finite memory and face uncertain environments, they may rely o...
Metabolic dysfunction-associated fatty liver disease (MAFLD), a global epidemic affecting 25% of adults, is driven by immune-metabolic dysregulation, yet the causal mechanisms linking immune cell-specific gene perturbations to disease progression rem...
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