LEADER 04345nam 2200733 450 001 9910133842303321 005 20221206100153.0 024 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(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 LEADER 02066oam 2200553 450 001 9910706760603321 005 20180110114550.0 035 $a(CKB)5470000002457851 035 $a(OCoLC)896810053 035 $a(OCoLC)995470000002457851 035 $a(EXLCZ)995470000002457851 100 $a20141123d1970 ua 0 101 0 $aeng 135 $aurmn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aGeology of the salt anticline region in southwestern Colorado /$fby Fred W. Cater; with a section on stratigraphy, by Fred W. Cater and Lawrence C. Craig; prepared on behalf of the U.S. Atomic Energy Commission 210 1$aWashington :$cUnited States Department of the Interior, Geological Survey,$d1970. 215 $a1 online resource (iv, 80 pages) $cillustrations, maps 225 1 $aGeological Survey professional paper ;$v637 300 $aTitle from title screen (viewed September 30, 2014). 300 $a"A study of the stratigraphy, structure, and geomorphology of an area characterized by large salt-cored anticlines, with a discussion of the growth of the salt cores." 320 $aIncludes bibliographical references (pages 72-75) and index. 606 $aGeology$zColorado 606 $aSalt deposits$zColorado 606 $aAnticlines$zColorado 606 $aGeology$2fast 606 $aSalt deposits$2fast 607 $aColorado$2fast 615 0$aGeology 615 0$aSalt deposits 615 0$aAnticlines 615 7$aGeology. 615 7$aSalt deposits. 700 $aCater$b Fred W$g(Fred William),$f1912-$01389778 702 $aCraig$b Lawrence C$g(Lawrence Carey),$f1918- 712 02$aGeological Survey (U.S.), 712 02$aU.S. Atomic Energy Commission, 801 0$bCOP 801 1$bCOP 801 2$bOCLCO 801 2$bOCLCF 801 2$bOCLCA 801 2$bGPO 906 $aBOOK 912 $a9910706760603321 996 $aGeology of the salt anticline region in southwestern Colorado$93542825 997 $aUNINA