MACHINE LEARNING AND DEEP LEARNING IN COMPUTATIONAL TOXICOLOGY (HB 2023)

HONG H.

ISBN 10: 3031207297 ISBN 13: 9783031207297

Edit� par SPRINGER NP, 2023

Edition internationale

Neuf(s) Couverture rigide

Vendeur UK BOOKS STORE, London, LONDO, Royaume-Uni �valuation du vendeur 5 sur 5 �toiles

Vendeur AbeBooks depuis 11 mars 2024

Cet article sp�cifique n'est plus disponible.

Afficher tous les articles du vendeur Cr�er une demande de livres portant sur des articles similaires

Afficher tous les exemplaires de ce livre

A propos de cet article

Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability. N� de r�f. du vendeur CVS 9783031207297

Signaler cet article

Synopsis :

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.

� propos de l?auteur: Huixiao Hong is a Senior Biomedical Research and Biomedical Product Assessment Service (SBRBPAS) expert and the chief of Bioinformatics Branch, Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration (FDA), working on the scientific bases for regulatory applications of bioinformatics, cheminformatics, artificial intelligence, and genomics. Before joining the FDA, he was the manager of Bioinformatics Division of Z-Tech, an ICFI company. He held a research scientist position at Sumitomo Chemical Company in Japan and was a visiting scientist at National Cancer Institute at National Institutes of Health. He was also an associate professor and the director of Laboratory of Computational Chemistry at Nanjing University in China. Dr. Hong is a member of steering committee of OpenTox, a member of the board directors of US MidSouth Computational Biology and Bioinformatics Society, and in the leadership circle of US FDA modeling and simulation working group. He published more than 240 scientific papers with a Google Scholar h-index 60. He serves as an associate editor for Experimental Biology and Medicine and an editorial board member for multiple peer-reviewed journals. He received his Ph.D. from Nanjing University in China and conducted research in Leeds University in England.

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

D�tails bibliographiques

Titre : MACHINE LEARNING AND DEEP LEARNING IN ...
�diteur : SPRINGER NP
Date d'�dition : 2023
Reliure : Couverture rigide
Etat : New
Edition : Edition internationale

Meilleurs r�sultats de recherche sur AbeBooks

Image d'archives

Machine Learning and Deep Learning in Computational Toxicology

Unbekannt

Edit� par Springer, 2023

ISBN 10 : 3031207297 ISBN 13 : 9783031207297

Ancien ou d'occasion Couverture rigide

Vendeur : Buchpark, Trebbin, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Etat : Hervorragend. Zustand: Hervorragend | Seiten: 676 | Sprache: Englisch | Produktart: B�cher | 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. N� de r�f. du vendeur 41491736/1

Contacter le vendeur

Acheter D'occasion

EUR 92,81

Exp�dition �EUR 105
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image d'archives

Machine Learning and Deep Learning in Computational Toxicology (eng)

Hong, Huixiao

Edit� par Springer, 2023

ISBN 10 : 3031207297 ISBN 13 : 9783031207297

Neuf Couverture rigide

impression � la demande

Vendeur : Brook Bookstore On Demand, Napoli, NA, Italie

�valuation du vendeur 4 sur 5 �toiles

Etat : new. Questo � un articolo print on demand. N� de r�f. du vendeur T3NF9R9WM3

Contacter le vendeur

Acheter neuf

EUR 126,26

Exp�dition �EUR 11
Exp�dition depuis Italie vers Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image fournie par le vendeur

Machine Learning and Deep Learning in Computational Toxicology

Edit� par Springer, Berlin|Springer International Publishing|Springer, 2023

ISBN 10 : 3031207297 ISBN 13 : 9783031207297

Neuf Couverture rigide

impression � la demande

Vendeur : moluna, Greven, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 mach. N� de r�f. du vendeur 727139185

Contacter le vendeur

Acheter neuf

EUR 136,16

Exp�dition �EUR 48,99
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image fournie par le vendeur

Machine Learning and Deep Learning in Computational Toxicology

Huixiao Hong

Edit� par Springer, 2023

ISBN 10 : 3031207297 ISBN 13 : 9783031207297

Neuf Couverture rigide

impression � la demande

Vendeur : preigu, Osnabr�ck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Contacter le vendeur

Acheter neuf

EUR 141,20

Exp�dition �EUR 70
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 5 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Machine Learning and Deep Learning in Computational Toxicology

Huixiao Hong

Edit� par Springer Nature Switzerland, Springer International Publishing Feb 2023, 2023

ISBN 10 : 3031207297 ISBN 13 : 9783031207297

Neuf Couverture rigide

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 676 pp. Englisch. N� de r�f. du vendeur 9783031207297

Contacter le vendeur

Acheter neuf

EUR 160,49

Exp�dition �EUR 60
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 2 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Machine Learning and Deep Learning in Computational Toxicology

Huixiao Hong

Edit� par Springer International Publishing, 2023

ISBN 10 : 3031207297 ISBN 13 : 9783031207297

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Buch. Etat : 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. N� de r�f. du vendeur 9783031207297

Contacter le vendeur

Acheter neuf

EUR 160,49

Exp�dition �EUR 66,46
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Machine Learning and Deep Learning in Computational Toxicology

Huixiao Hong

Edit� par Springer International Publishing Feb 2023, 2023

ISBN 10 : 3031207297 ISBN 13 : 9783031207297

Neuf Couverture rigide

impression � la demande

Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 and deep 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. 676 pp. Englisch. N� de r�f. du vendeur 9783031207297

Contacter le vendeur