Diagnosis of Neurological Disorders Based on Deep Learning Techniques

This book provides a comprehensive overview of deep learning approaches for the diagnosis of neurological disorders, covering algorithms, models, and applications. It includes practical examples and data preprocessing techniques and is suitable for graduate students and researchers in the field.

Format: Hardback
Length: 222 pages
Publication date: 15 May 2023
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the realm of deep learning techniques, specifically focusing on their application in diagnosing neurological disorders. It provides a thorough exploration of deep learning algorithms, their fundamentals, and practical implementations, making it an invaluable resource for professionals and students alike.

The book begins by introducing the basics of deep learning algorithms, using clear and concise diagrams and data tables to facilitate understanding. It then delves into the specific applications of deep learning in diagnosing neurodegenerative and neurodevelopmental disorders. Readers will gain a deep understanding of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks, as well as their role in diagnosing various neurological conditions.

In addition to covering the theoretical aspects, the book emphasizes the practical aspects of deploying deep learning models for diagnosis. It provides detailed instructions on building, training, and evaluating deep architectures, as well as discussing the challenges and limitations associated with this approach. The book also includes real-time case studies and examples to illustrate the practical applications of deep learning in neurological disorders.

One of the key strengths of this book is its accessibility to both novice and experienced readers. It begins with a foundational overview of deep learning, gradually progressing to more advanced topics, ensuring that readers can build a strong understanding of the subject matter. The book is well-organized, with clear headings and subheadings that guide readers through each chapter.

Furthermore, the book is extensively referenced, providing readers with a wealth of additional resources for further exploration. It includes a comprehensive list of relevant publications, research papers, and online resources that can help readers deepen their knowledge and stay up-to-date with the latest developments in the field.

Overall, this book is a must-read for anyone interested in leveraging deep learning techniques for diagnosing neurological disorders. It offers a comprehensive and up-to-date overview of the subject matter, providing valuable insights and practical guidance for professionals and students alike.

Weight: 444g
Dimension: 158 x 235 x 21 (mm)
ISBN-13: 9781032325231