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Titlebook: Computational Neurosurgery; Antonio Di Ieva,Eric Suero Molina,Carlo Russo Book 2024 The Editor(s) (if applicable) and The Author(s), under

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發(fā)表于 2025-3-21 18:45:15 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Computational Neurosurgery
編輯Antonio Di Ieva,Eric Suero Molina,Carlo Russo
視頻videohttp://file.papertrans.cn/243/242258/242258.mp4
概述Brings computational neuroscience to neurosurgery.First book on this emerging new field.The focus is primarily clinical, and there is a solid foundation of research aspects
叢書(shū)名稱Advances in Experimental Medicine and Biology
圖書(shū)封面Titlebook: Computational Neurosurgery;  Antonio Di Ieva,Eric Suero Molina,Carlo Russo Book 2024 The Editor(s) (if applicable) and The Author(s), under
描述.This comprehensive and authoritative reference presents the state-of-the-art computational methods applied to the field of neurosurgery. The book brings together leading neuroscientists, neurosurgeons, mathematicians, computer scientists, engineers, ethicists and lawyers, to open the new frontier of computational neurosurgery to a broad audience interested in the translational field of the application of computational models, such as deep learning, to the study of the brain and the practical applications of neurosurgery. The focus is primarily clinical, and there is a solid foundation of research aspects. With forewords by Michael L.J. Apuzzo and Enrico Coiera, the book is organized into 2 sections: (1) tenets of computational modeling, artificial intelligence, computational analysis, and analysis software; (2) computational neurosurgery applications, including neurodiagnostics, neuro-oncology, vascular neurosurgery, all the neurosurgical disciplines, surgical approaches, intraoperative applications, and ethics and legal aspects..
出版日期Book 2024
關(guān)鍵詞deep learning; artificial intelligence; brain; neuroscience; neurosurgery; computational neuroscience; neu
版次1
doihttps://doi.org/10.1007/978-3-031-64892-2
isbn_softcover978-3-031-64894-6
isbn_ebook978-3-031-64892-2Series ISSN 0065-2598 Series E-ISSN 2214-8019
issn_series 0065-2598
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Navigating Mathematical Basics: A Primer for Deep Learning in Science crash course, our presentation is kept in the context of deep learning and machine learning models including the sigmoid model, the softmax model, and fully connected feedforward deep neural networks. We also hint at basic mathematical objects appearing in neural networks for images and text data.
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Applications and Integration of Radiomics for Skull Base Oncologydiomic applications, contrast-enhanced T1-weighted MRI images remain the most utilized sequence for model development. Efforts to standardize and connect radiomic features to tumor biology have facilitated more clinically applicable radiomic models. Despite the advancement in model performance, seve
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0065-2598 luding neurodiagnostics, neuro-oncology, vascular neurosurgery, all the neurosurgical disciplines, surgical approaches, intraoperative applications, and ethics and legal aspects..978-3-031-64894-6978-3-031-64892-2Series ISSN 0065-2598 Series E-ISSN 2214-8019
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發(fā)表于 2025-3-23 08:47:28 | 只看該作者
Book 2024tificial intelligence, computational analysis, and analysis software; (2) computational neurosurgery applications, including neurodiagnostics, neuro-oncology, vascular neurosurgery, all the neurosurgical disciplines, surgical approaches, intraoperative applications, and ethics and legal aspects..
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