Medical Diagnosis Using Artificial Neural Networks

Medical Diagnosis Using Artificial Neural Networks

Sara Moein (Washington University in Saint Louis, USA)
Indexed In: SCOPUS
Release Date: June, 2014|Copyright: © 2014 |Pages: 310
ISBN13: 9781466661462|ISBN10: 1466661461|EISBN13: 9781466661479|DOI: 10.4018/978-1-4666-6146-2

Description

Advanced conceptual modeling techniques serve as a powerful tool for those in the medical field by increasing the accuracy and efficiency of the diagnostic process. The application of artificial intelligence assists medical professionals to analyze and comprehend a broad range of medical data, thus eliminating the potential for human error.

Medical Diagnosis Using Artificial Neural Networks introduces effective parameters for improving the performance and application of machine learning and pattern recognition techniques to facilitate medical processes. This book is an essential reference work for academicians, professionals, researchers, and students interested in the relationship between artificial intelligence and medical science through the use of informatics to improve the quality of medical care.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Artificial Neural Network
  • Disease Diagnosis
  • Heart Disorders
  • Intelligent Medical Diagnosis
  • Neural Network Optimization
  • Swarm Intelligence

Reviews and Testimonials

This volume considers the use of artificial intelligence, particularly artificial neural networks, in medical diagnosis. It explains the definition of medical diagnosis and the techniques used to improve the performance of existing medical diagnosis systems, the difficulties of diagnosis, and the components of web-based medical diagnosis systems; the definition of artificial intelligence, its importance in diagnosis, and applications like signal and image processing; the procedure and steps for diagnosis; the biological and mathematical definitions of artificial neural networks and the activation functions for processing; types of artificial neural networks and definitions related to feed forward and recurrent neural networks; other terms and definitions; and applications for medical research.

– ProtoView Book Abstracts (formerly Book News, Inc.)

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Sara Moein, PhD, is currently a researcher at Washington University in Saint Louis, United States. Her interests are intelligent medical diagnosis, machine learning, algorithm designing, artificial neural network and computational biology. She has received her PhD from Multimedia University, Malaysia in biomedical engineering. Her Master and Bachelor degrees are in software engineering. She is designer of a new brand optimization algorithm namely Kinetic Gas Molecule Optimization (KGMO). Dr. Sara Moein is the member of editorial boards of some of the international journals such as Journal of Experimental & Theoretical Artificial Intelligence and International Journal of Computer Applications and others. In addition she is reviewer of many journals and conferences papers such as Journal of Computing, Journal of Supercomputing and conferences such as ICINCO (2012-2014), WORLDCOMP (2009-2013) and 7th IEEE BIBE. She has a number of publications in book chapters, journals, and conference proceedings. She is also member of International Society of Intelligent Biological Medicine and member of technical committee of International Association of Science and Technology for Development (IASTAD), Canada, 2012-2015.

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