Our fingers are the most dexterous and complicated parts of our body and play a significant role in our daily activities. Non-invasive techniques, such as Electroencephalography (EEG) and Electromyography (EMG) can be used to collect neural and muscular signals related to finger movements. In this study, we combined an 8-channel EMG and a 31-channel EEG while the human subject moved one of the five fingers on the right hand.
View Article and Find Full Text PDFRenal vein entrapment, especially concerning the right renal vein, represents a scarcely explored anatomical aberration. The right renal vein's pivotal role in renovascular renal hemodynamics underlines the clinical significance of its compression, which can precipitate an elevated renal venous pressure gradient in relation to the inferior vena cava. This report delineates a unique instance of right renal vein entrapment in a 92-year-old male cadaver, identified during routine dissection.
View Article and Find Full Text PDFBackground This study aimed to demonstrate both the potential and development progress in the identification of extracapsular nodal extension in head and neck cancer patients prior to surgery. Methodology A deep learning model has been developed utilizing multilayer gradient mapping-guided explainable network architecture involving a volume extractor. In addition, the gradient-weighted class activation mapping approach has been appropriated to generate a heatmap of anatomic regions indicating why the algorithm predicted extension or not.
View Article and Find Full Text PDFThis article is a case study that discusses the development and implementation of an internal learning object repository (LOR) for a large national organization with a distributed working environment. It describes the organizational environment and why an internal LOR was needed. It describes technical considerations, including the various document management systems (DMS) available, and why an open source DMS was selected to use as an internal LOR.
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