Overview

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.

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9781466661493

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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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