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Titlebook: Internet of Things of Big Data for Healthcare; 5th International Wo Jun Qi,Po Yang Conference proceedings 2024 The Editor(s) (if applicable

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樓主: 萬能
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發(fā)表于 2025-3-23 12:42:17 | 只看該作者
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發(fā)表于 2025-3-24 00:48:51 | 只看該作者
,Adaptive Prior Correction in?Alzheimer’s Disease Spatio-Temporal Modeling via?Multi-task Learning, utilizing prior constraints. However, the existing models do not explicitly model the spatio-temporal connectivity for the lack of samples and prior medical knowledge. In this article, we propose a sparse multi-task learning model for cognitive status prediction, which is adaptively weighted in spa
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發(fā)表于 2025-3-24 05:30:41 | 只看該作者
An Electromyographic Signal Acquisition System for Sarcopenia,ia requires the utilization of extensive and cumbersome testing equipment. Surface electromyography (sEMG) is able to track muscle status and has been effectively employed in diagnosing various diseases or human-machine interactions, but its application in sarcopenia detection remains unexplored. In
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發(fā)表于 2025-3-24 12:02:15 | 只看該作者
,A Comparative Study of?ResNet and?DenseNet in?the?Diagnosis of?Colitis Severity,tis colonoscopy images, relying extensively on their clinical expertise. The accuracy of these assessments is of utmost importance in guiding subsequent treatment strategies for individuals with colitis. Several deep learning models have demonstrated their efficacy in the domain of medical imaging,
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發(fā)表于 2025-3-24 15:37:01 | 只看該作者
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發(fā)表于 2025-3-25 00:01:52 | 只看該作者
https://doi.org/10.1007/978-3-031-52216-1artificial intelligence; health informatics; biomedical engineering; information fusion; medical images;
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