Isbn: 9783031207327 - machine learning and deep learning in computational toxicology (computational methods in engineering & the sciences) (2 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer, 2024

    3031207327 / 9783031207327

    Serie: Buch 3 von 5 - Computational Methods in Engineering & the Sciences

    • Softcover

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    Taschenbuch. Zustand: Neu. Machine Learning and Deep Learning in Computational Toxicology | Huixiao Hong | Taschenbuch | Computational Methods in Engineering & the Sciences | xix | Englisch | 2024 | Springer | EAN 9783031207327 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Sprache: Englisch

    Verlag: Springer, 2024

    3031207327 / 9783031207327

    Serie: Buch 3 von 5 - Computational Methods in Engineering & the Sciences

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology. This book is expected to provide a reference for practical applications of machine learning anddeep learning in toxicological research. It is a useful guide for toxicologists, chemists, drug discovery and development researchers, regulatory scientists, government reviewers, and graduate students. The main benefit for the readers is understanding the widely used machine learning and deep learning techniques and gaining practical procedures for applying machine learning and deep learning in predictive toxicology.…