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In hospitalized older patients with AF, there is still a high prevalence of inappropriate OAC prescribing. Characteristics usually related to frailty are associated with the inappropriate prescribing. These findings point to the need for targeted interventions designed for internists and geriatricians, aimed at improving the appropriate prescribing of OACs in this complex and high-risk population.

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The precise delineation of brain cancer is a crucial task during surgery. There are several techniques employed during surgical procedures to guide neurosurgeons in the tumor resection. However, hyperspectral imaging (HSI) is a promising non-invasive and non-ionizing imaging technique that could improve and complement the currently used methods. The HypErspectraL Imaging Cancer Detection (HELICoiD) European project has addressed the development of a methodology for tumor tissue detection and delineation exploiting HSI techniques. In this approach, the K-means algorithm emerged in the delimitation of tumor borders, which is of crucial importance. The main drawback is the computational complexity of this algorithm. This paper describes the development of the K-means clustering algorithm on different parallel architectures, in order to provide real-time processing during surgical procedures. This algorithm will generate an unsupervised segmentation map that, combined with a supervised classification map, will offer guidance to the neurosurgeon during the tumor resection task. We present parallel K-means clustering based on OpenMP, CUDA and OpenCL paradigms. These algorithms have been validated through an in-vivo hyperspectral human brain image database. Experimental results show that the CUDA version can achieve a speed-up of ~ 150 × with respect to a sequential processing. The remarkable result obtained in this paper makes possible the development of a real-time classification system.

Our study confirms a dramatic phrenic nerve involvement in absence of clinical and laboratory evidence of diaphragmatic weakness; further studies and an adequate follow-up are necessary to discover whether the disease progress might encompass respiratory dysfunction at later stages.