Handbook Of Decision Support Systems For Neurological Disorders (Original PDF From Publisher)

Handbook Of Decision Support Systems For Neurological Disorders (Original PDF From Publisher)

Edition

1

File Size

6.72 MB

Format

Publisher PDF

Language

‎English

Publisher

Elsevier

ISBN-10

9780128222713

$25.00

5/5
Description

Handbook Of Decision Support Systems For Neurological Disorders (Original PDF From Publisher)

1.1.Description

“Handbook of Decision Support Systems for Neurological Disorders”  offers comprehensive coverage of advanced computer-aided diagnosis systems specifically designed for neurological disorders.

While existing computer-aided decision support systems focus on various medical imaging modalities, this groundbreaking book is the first to concentrate solely on neurological disorders.

Given the rising prevalence of conditions such as Alzheimer’s, Parkinson’s, and Dementia, the content of this book holds significant importance in the medical field.

The topics explored encompass recent computational approaches, various types of neurological disorders, and cutting-edge technologies such as deep convolution neural networks, generative adversarial networks, autoencoders, recurrent neural networks, and modified/hybrid artificial neural networks.

“Handbook of Decision Support Systems for Neurological Disorders” addresses the growing demand for sophisticated decision support systems in the field of neurology.

 

Handbook Of Decision Support Systems For Neurological Disorders

Handbook Of Decision Support Systems For Neurological Disorders

 

1.2.Key Features

The key features of the “Handbook of Decision Support Systems for Neurological Disorders” include comprehensive coverage of advanced computer-aided diagnosis systems tailored for neurological disorders. The book addresses the increasing prevalence of conditions like Alzheimer’s, Parkinson’s, and Dementia.

It explores recent computational approaches, various neurological disorders, and advanced technologies such as deep convolution neural networks, generative adversarial networks, autoencoders, recurrent neural networks, and modified/hybrid artificial neural networks.

“Handbook of Decision Support Systems for Neurological Disorders” is essential for professionals in the medical field seeking sophisticated decision support systems to enhance the diagnosis and management of neurological disorders.

 

Handbook Of Decision Support Systems For Neurological Disorders

Handbook Of Decision Support Systems For Neurological Disorders

 

1.3. About Writer

  1. Jude Hemanth is an esteemed editor known for his significant contributions to the field of computational intelligence and biomedical engineering.
  2. With a distinguished career, Hemanth has played a pivotal role in advancing research at the intersection of computer science and healthcare. His expertise lies in the development and application of decision support systems, particularly in the context of neurological disorders. Hemanth has demonstrated a keen interest in leveraging computational approaches, including neural networks and artificial intelligence, to enhance the diagnosis and management of complex medical conditions. As an editor, he has been instrumental in curating knowledge and insights, fostering advancements in the critical area of decision support systems for neurological disorders. Hemanth’s work continues to make a profound impact, providing valuable resources for professionals and researchers in the medical and computational fields alike.

 

Handbook Of Decision Support Systems For Neurological Disorders

Handbook Of Decision Support Systems For Neurological Disorders

 

Summary

The “Handbook of Decision Support Systems for Neurological Disorders” is a comprehensive resource that focuses on advanced computer-aided diagnosis systems tailored specifically for neurological disorders.

In response to the growing prevalence of conditions like Alzheimer’s, Parkinson’s, and Dementia, the book delves into recent computational approaches, encompassing deep convolution neural networks, generative adversarial networks, autoencoders, recurrent neural networks, and modified/hybrid artificial neural networks.

By concentrating solely on decision support systems for neurological disorders, the handbook addresses a critical need in the medical field.

It provides a thorough exploration of cutting-edge technologies and methodologies, offering valuable insights for researchers, medical professionals, and practitioners involved in the diagnosis and treatment of neurological conditions.

 

 

 

 

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