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024 7 $a10.1109/9780470545355
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035   $a(IEEE)5263228
035   $a(PPN)264393864
035   $a(OCoLC)798700382
035   $a(EXLCZ)993280000000033541
100   $a20100317h20152000  uy             0
101 0 $aeng
135   $aur|n|||||||||
181   $ctxt
182   $cc
183   $acr
200 10$aNeural networks and artificial intelligence for biomedical engineering /$fDonna L. Hudson, Maurice E. Cohen
210  1$aNew York :$cInstitute of Electrical and Electronics Engineers,$dc2000.
210  2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[1999]
215   $a1 PDF (xxiii, 306 pages) $cillustrations
225 1 $aIEEE press series on biomedical engineering ;$v3
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a0-470-54535-6 
311   $a0-7803-3404-3 
320   $aIncludes bibliographical references and index.
327   $aPreface. Acknowledgments. Overview. NEURAL NETWORKS. Foundations of Neural Networks. Classes of Neural Networks. Classification Networks and Learning. Supervised Learning. Unsupervised Learning. Design Issues. Comparative Analysis. Validation and Evaluation. ARTIFICIAL INTELLIGENCE. Foundation of Computer-Assisted Decision Making. Knowledge Representation. Knowledge Acquisition. Reasoning Methodologies. Validation and Evaluation. ALTERNATIVE APPROACHES. Genetic Algorithms. Probabilistic Systems. Fuzzy Systems. Hybrid Systems. HyperMerge, a Hybird Expert System. Future Perspectives. Index. About the Authors.
330   $aUsing examples drawn from biomedicine and biomedical engineering, this essential reference book brings you comprehensive coverage of all the major techniques currently available to build computer-assisted decision support systems. You will find practical solutions for biomedicine based on current theory and applications of neural networks, artificial intelligence, and other methods for the development of decision aids, including hybrid systems. Neural Networks and Artificial Intelligence for Biomedical Engineering offers students and scientists of biomedical engineering, biomedical informatics, and medical artificial intelligence a deeper understanding of the powerful techniques now in use with a wide range of biomedical applications. Highlighted topics include: . Types of neural networks and neural network algorithms. Knowledge representation, knowledge acquisition, and reasoning methodologies. Chaotic analysis of biomedical time series. Genetic algorithms. Probability-based systems and fuzzy systems. Evaluation and validation of decision support aids. An Instructor Support FTP site is available from the Wiley editorial department: ftp://ftp.ieee.org/uploads/press/hudson.
410  0$aIEEE Press series in biomedical engineering ;$v3
606   $aArtificial intelligence$xMedical applications
606   $aNeural networks (Computer science)$xComputer simulation
606   $aExpert systems (Computer science)
606   $aBiomedical engineering
606   $aNeural Networks, Computer
606   $aBiomedical Engineering
606   $aExpert Systems
606   $aArtificial Intelligence
615  0$aArtificial intelligence$xMedical applications
615  0$aNeural networks (Computer science)$xComputer simulation
615  0$aExpert systems (Computer science)
615  0$aBiomedical engineering
615 22$aNeural Networks, Computer.
615 22$aBiomedical Engineering.
615 22$aExpert Systems.
615 12$aArtificial Intelligence.
676   $a610/.285/63
700   $aHudson$b D. L.$g(Donna L.)$0845659
701   $aCohen$b M. E$g(Maurice E.)$0845660
801  0$bCaBNVSL
801  1$bCaBNVSL
801  2$bCaBNVSL
906   $aBOOK
912   $a9910133842303321
996   $aNeural networks and artificial intelligence for biomedical engineering$91887881
997   $aUNINA