LEADER 04345nam 2200733 450 001 9910829981803321 005 20240219140204.0 024 7 $a10.1109/9780470545355 035 $a(CKB)3280000000033541 035 $a(SSID)ssj0000441618 035 $a(PQKBManifestationID)12160868 035 $a(PQKBTitleCode)TC0000441618 035 $a(PQKBWorkID)10406914 035 $a(PQKB)10162894 035 $a(CaBNVSL)mat05263228 035 $a(IDAMS)0b000064810c33d0 035 $a(IEEE)5263228 035 $a(OCoLC)798700382 035 $a(PPN)264393864 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. 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