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Using examples drawn from biomedicine and biomedical engineering, this essential reference book brings you comprehensive coverage of all the major techniques currently available to build computer-assisted decision support systems. You will find practical solutions for biomedicine based on current theory and applications of neural networks, artificial intelligence, and other methods for the development of decision aids, including hybrid systems. Neural Networks and Artificial Intelligence for Biomedical Engineering offers students and scientists of biomedical engineering, biomedical informatics, and medical artificial intelligence a deeper understanding of the powerful techniques now in use with a wide range of biomedical applications. Highlighted topics include: . Types of neural networks and neural network algorithms. Knowledge representation, knowledge acquisition, and reasoning methodologies. Chaotic analysis of biomedical time series. Genetic algorithms. Probability-based systems and fuzzy systems. Evaluation and validation of decision support aids. An Instructor Support FTP site is available from the Wiley editorial department: ftp://ftp.ieee.org/uploads/press/hudson.
Artificial intelligence --- Neural networks (Computer science) --- Expert systems (Computer science) --- Biomedical engineering --- Neural Networks, Computer. --- Biomedical Engineering. --- Expert Systems. --- Artificial Intelligence. --- Medical applications --- Computer simulation --- Expert systems (Computer science). --- Neural networks (Computer science). --- Medical applications. --- Computer simulation. --- #TELE:SISTA --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Natural computation --- Soft computing --- Knowledge-based systems (Computer science) --- Systems, Expert (Computer science) --- Computer systems --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Data processing --- Artificial intelligence - Medical applications --- Biomedical engineering - Computer simulation
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Clinical medicine --- Decision Making, Computer-Assisted. --- Decision support systems. --- Fuzzy Logic. --- Heart --- Decision making --- Data processing. --- Diseases --- Treatment --- Case studies.
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