Handbook of Computational Neurodegeneration (Hardcover, 1st ed. 2022)

The Handbook of Computational Neurodegeneration provides a comprehensive overview of the field and thus bridges the gap between standard textbooks of research on neurodegeneration and dispersed publications for specialists that have a narrowed focus on computational methods to study this complicated process. The handbook reviews the central issues and methodological approaches related to the field for which the reader pursues a thorough overview. It also conveys more advanced knowledge, thus serving both as an introductory text and as a starting point for an in-depth study of a specific area, as well as a quick reference source for the expert by reflecting the state of the art and future prospects. The book includes topics that are usually missing in standard textbooks and that are only marginally represented in the specific literature. The broad scope of this handbook is reflected by five major parts that facilitate an integration of computational concepts, methods and applications in the study of neurodegeneration. Each part is intended to stand on its own, giving an overview of the topic and the most important problems and approaches, which are supported by examples, practical applications, and proposed methodologies. The basic concepts and knowledge, standard procedures and methods are presented, as well as recent advances and new perspectives.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	June 2022
First published:	2022
Editors:	Panayiotis Vlamos • Ilias S. Kotsireas • Ioannis Tarnanas
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover • Electronic book text
Edition:	1st ed. 2022
ISBN-13:	978-3-319-75923-4
Categories:	Books > Medicine > General issues > Medical equipment & techniques > General Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences
LSN:	3-319-75923-X
Barcode:	9783319759234

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