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Titlebook: Machine Learning in Medical Imaging; 9th International Wo Yinghuan Shi,Heung-Il Suk,Mingxia Liu Conference proceedings 2018 Springer Nature

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Cheng Chen,Qi Dou,Hao Chen,Pheng-Ann Heng evaluation of the patient to define the degree of target-organ damage and to assess physiologic derangements. In this chapter autonomic contributions to blood pressure control will be reviewed briefly, followed by a more complete discussion of those agents which interfere with autonomic mechanisms
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Mingli Zhang,Christian Desrosiers,Yuhong Guo,Caiming Zhang,Budhachandra Khundrakpam,Alan Evansased on their activities in the current week. The result is an instance of the family of absorbing Markov chains, which can be analysed using the property called time to absorption. The preliminary results show that interesting patterns in student VLE behaviour can be uncovered, especially when comb
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Weixiang Chen,Hongchen Ji,Jianjiang Feng,Rong Liu,Yi Yu,Ruiquan Zhou,Jie Zhous to date. The research discussed in this paper shows how personalized and scrutable visual narratives encouraged students, enrolled into an adaptive OLE as part of their undergraduate degree program, to study their course content and subsequently improve their knowledge levels.
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Developing Novel Weighted Correlation Kernels for Convolutional Neural Networks to Extract Hierarche point, thus conveying the richer interaction information of brain regions compared with the PCC method. Furthermore, we propose a wc-kernel based convolutional neural network (CNN) (called wck-CNN) framework for extracting the hierarchical (., from low-order to high-order) functional connectivitie
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Robust Contextual Bandit via the Capped-, Norm for Mobile Health Intervention,a result, the robustness of both actor-critic updating is enhanced. There is a key parameter in the capped-. norm. We provide a reliable method to properly set it by making use of one of the most fundamental definitions of outliers in statistics. Extensive experiment results demonstrate that our met
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