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System for planning and/or providing neuromodulation

Grégoire Courtine, Vincent Delattre, Marco Capogrosso, Fabien Bertrand Paul Wagner, Karen Minassian
2021
Patent
Abstract

The present invention relates to systems and methods for planning and/or providing neuromodulation One example system includesa stimulation related basic data storage module for storing stimulation related basic data,a stimulation related response data storage module for storing the stimulation related response data,a transfer module configured such that the stimulation related basic data are linked with and/or translated into the response data and/or artificial response data created by the transfer module, wherein the data generated by the transfer module are transfer data, the transfer data comprising link data and/or translation data and/or artificial response data,mapping module configured and arranged such that based on the stimulation related basic data and stimulation related response data and the transfer data a digital characteristic map is generated, andan analysis module configured and arranged such that the digital characteristic map is analyzed automatically.

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Ontological neighbourhood
Information engineering
Related concepts (29)
Machine translation
Machine translation is use of either rule-based or probabilistic (i.e. statistical and, most recently, neural network-based) machine learning approaches to translation of text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. History of machine translation The origins of machine translation can be traced back to the work of Al-Kindi, a ninth-century Arabic cryptographer who developed techniques for systemic language translation, including cryptanalysis, frequency analysis, and probability and statistics, which are used in modern machine translation.
Translation
Translation is the communication of the meaning of a source-language text by means of an equivalent target-language text. The English language draws a terminological distinction (which does not exist in every language) between translating (a written text) and interpreting (oral or signed communication between users of different languages); under this distinction, translation can begin only after the appearance of writing within a language community.
Neural machine translation
Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model. They require only a fraction of the memory needed by traditional statistical machine translation (SMT) models. Furthermore, unlike conventional translation systems, all parts of the neural translation model are trained jointly (end-to-end) to maximize the translation performance.
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