Titlebook: Introduction to Deep Learning for Healthcare; Cao Xiao,Jimeng Sun Textbook 2021 The Editor(s) (if applicable) and The Author(s), under exc

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Malfunction

两种语言

Deep Neural Networks (DNN),pproximators that accurately map input data . to output . (i.e., to learn a function .(.) ≈ .) through multiple layers of nonlinear transformations. Such a design enables neural networks to perform tasks like classification and regression.

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Recurrent Neural Networks (RNN),o prominent RNN models, namely long short-term memory (LSTM), and gated recurrent unit (GRU) have gained popularity since they alleviate technical challenges related to capturing long-term dependencies and addressing vanishing gradient problems.

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https://doi.org/10.1007/978-3-030-82184-5Deep learning; healthcare applications; deep neural networks; Clinical predictive model; x-ray classific

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tions shape performing and theatrical tasks by means of an embodied pedagogy. In this chapter, I focus on the idea of genealogy applied to theatre laboratories by looking at the example of Odin Teatret and reframe genealogy as the felt relationship amongst ideas, bodies and practices, rather than a

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