Neural networks and artificial intelligence for biomedical engineering / (Record no. 73830)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 06502nam a2201489 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 5263228 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220712205629.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 100317t20152000nyua ob 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780470545355 |
| -- | electronic |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| -- | electronic |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 610/.285/63 |
| 100 1# - AUTHOR NAME | |
| Author | Hudson, D. L., |
| 245 10 - TITLE STATEMENT | |
| Title | Neural networks and artificial intelligence for biomedical engineering / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 PDF (xxiii, 306 pages) : |
| 490 1# - SERIES STATEMENT | |
| Series statement | IEEE press series on biomedical engineering ; |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Preface. 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| Subject | Artificial intelligence |
| General subdivision | Medical applications. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| Subject | Neural networks (Computer science) |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| Subject | Expert systems (Computer science) |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| Subject | Biomedical engineering |
| General subdivision | Computer simulation. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Cohen, M. E. |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5263228 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | New York : |
| -- | Institute of Electrical and Electronics Engineers, |
| -- | c2000. |
| 264 #2 - | |
| -- | [Piscataqay, New Jersey] : |
| -- | IEEE Xplore, |
| -- | [1999] |
| 336 ## - | |
| -- | text |
| -- | rdacontent |
| 337 ## - | |
| -- | electronic |
| -- | isbdmedia |
| 338 ## - | |
| -- | online resource |
| -- | rdacarrier |
| 588 ## - | |
| -- | Description based on PDF viewed 12/21/2015. |
| 695 ## - | |
| -- | Accuracy |
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| -- | Algorithm design and analysis |
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| -- | Arteries |
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| -- | Artificial intelligence |
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| -- | Artificial neural networks |
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| -- | Bayesian methods |
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| -- | Binary trees |
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| -- | Biographies |
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| -- | Biological cells |
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| -- | Biological neural networks |
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| -- | Biological system modeling |
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| -- | Biomedical imaging |
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| -- | Blood |
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| -- | Blood pressure |
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| -- | Brain models |
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| -- | Chaos |
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| -- | Classification algorithms |
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| -- | Clustering algorithms |
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| -- | Cognition |
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| -- | Computational modeling |
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| -- | Computers |
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| -- | Convergence |
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| -- | Data models |
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| -- | Databases |
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| -- | Decision making |
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| -- | Decision trees |
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| -- | Design automation |
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| -- | Diseases |
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| -- | Drugs |
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| -- | Electric potential |
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| -- | Electrocardiography |
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| -- | Electroencephalography |
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| -- | Engines |
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| -- | Euclidean distance |
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| -- | Expert systems |
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| -- | Feature extraction |
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| -- | Fires |
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| -- | Fuzzy sets |
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| -- | Genetics |
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| -- | Gold |
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| -- | Heart |
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| -- | Hopfield neural networks |
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| -- | Hospitals |
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| -- | Humans |
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| -- | Indexes |
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| -- | Inference algorithms |
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| -- | Knowledge acquisition |
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| -- | Knowledge based systems |
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| -- | Knowledge representation |
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| -- | Linear matrix inequalities |
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| -- | Mathematical model |
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| -- | Measurement |
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| -- | Medical diagnostic imaging |
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| -- | Medical services |
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| -- | Natural language processing |
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| -- | Neurons |
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| -- | Numerical models |
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| -- | Object oriented modeling |
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| -- | Optimization |
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| -- | Organisms |
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| -- | Pain |
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| -- | Partitioning algorithms |
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| -- | Probabilistic logic |
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| -- | Process control |
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| -- | Production |
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| -- | Search problems |
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| -- | Simulated annealing |
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| -- | Software |
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| -- | Spectroscopy |
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| -- | Supervised learning |
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| -- | Support vector machine classification |
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| -- | Testing |
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| -- | Tiles |
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| -- | Time series analysis |
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| -- | Training |
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| -- | Transforms |
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| -- | Unsupervised learning |
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| -- | Vectors |
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