| 000 | 05227nam a22005175i 4500 | ||
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| 001 | 978-0-387-69319-4 | ||
| 003 | DE-He213 | ||
| 005 | 20250710084010.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100301s2007 xxu| s |||| 0|eng d | ||
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_a9780387693194 _a99780387693194 |
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| 024 | 7 |
_a10.1007/978-0-387-69319-4 _2doi |
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| 082 | 0 | 4 |
_a610 _223 |
| 100 | 1 |
_aPardalos, Panos M. _eeditor. |
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| 245 | 1 | 0 |
_aData Mining in Biomedicine _h[recurso electrónico] / _cedited by Panos M. Pardalos, Vladimir L. Boginski, Alkis Vazacopoulos. |
| 264 | 1 |
_aBoston, MA : _bSpringer US, _c2007. |
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| 300 |
_aXVII, 579 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_arecurso en línea _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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| 490 | 1 |
_aSpringer Optimization and Its Applications, _x1931-6828 ; _v7 |
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| 505 | 0 | _aRecent Methodological Developments for Data Mining Problems in Biomedicine -- Pattern-Based Discriminants in the Logical Analysis of Data -- Exploring Microarray Data with Correspondence Analysis -- An Ensemble Method of Discovering Sample Classes Using Gene Expression Profiling -- CpG Island Identification with Higher Order and Variable Order Markov Models -- Data Mining Algorithms for Virtual Screening of Bioactive Compounds -- Sparse Component Analysis: a New Tool for Data Mining -- Data Mining Via Entropy and Graph Clustering -- Molecular Biology and Pooling Design -- An Optimization Approach to Identify the Relationship between Features and Output of a Multi-label Classifier -- Classifying Noisy and Incomplete Medical Data by a Differential Latent Semantic Indexing Approach -- Ontology Search and Text Mining of MEDLINE Database -- Data Mining Techniques in Disease Diagnosis -- Logical Analysis of Computed Tomography Data to Differentiate Entities of Idiopathic Interstitial Pneumonias -- Diagnosis of Alport Syndrome by Pattern Recognition Techniques -- Clinical Analysis of the Diagnostic Classification of Geriatric Disorders -- Data Mining Studies in Genomics and Proteomics -- A Hybrid Knowledge Based-Clustering Multi-Class SVM Approach for Genes Expression Analysis -- Mathematical Programming Formulations for Problems in Genomics and Proteomics -- Inferring the Origin of the Genetic Code -- Deciphering the Structures of Genomic DNA Sequences Using Recurrence Time Statistics -- Clustering Proteomics Data Using Bayesian Principal Component Analysis -- Bioinformatics for Traumatic Brain Injury: Proteomic Data Mining -- Characterization and Prediction of Protein Structure -- Computational Methods for Protein Fold Prediction: an Ab-initio Topological Approach -- A Topological Characterization of Protein Structure -- Applications of Data Mining Techniques to Brain Dynamics Studies -- Data Mining in EEG: Application to Epileptic Brain Disorders -- Information Flow in Coupled Nonlinear Systems: Application to the Epileptic Human Brain -- Reconstruction of Epileptic Brain Dynamics Using Data Mining Techniques -- Automated Seizure Prediction Algorithm and its Statistical Assessment: A Report from Ten Patients -- Seizure Predictability in an Experimental Model of Epilepsy -- Network-Based Techniques in EEG Data Analysis and Epileptic Brain Modeling. | |
| 520 | _aThis volume presents an extensive collection of chapters covering various aspects of the exciting and important research area of data mining techniques in biomedicine. The topics include: - new approaches for the analysis of biomedical data, - applications of data mining techniques to real-life problems in medical practice, - comprehensive reviews of recent trends in the field. The book addresses the problems arising in fundamental areas of biomedical research, such as genomics, proteomics, protein characterization, and neuroscience. This volume would be of interest to scientists and practitioners working in the field of biomedicine, as well as related areas of engineering, mathematics, and computer science. It can also be helpful to graduate students and young researchers looking for new exciting directions in their work. Since each chapter can be read independently, readers interested in specific problems and applications may find the material of certain chapters useful. | ||
| 650 | 0 | _aMEDICINE. | |
| 650 | 0 | _aMATHEMATICS. | |
| 650 | 0 | _aOPERATIONS RESEARCH. | |
| 650 | 0 | _aSTATISTICS. | |
| 650 | 0 | _aBIOMEDICAL ENGINEERING. | |
| 650 | 1 | 4 | _aBIOMEDICINE. |
| 650 | 2 | 4 | _aBIOMEDICINE GENERAL. |
| 650 | 2 | 4 | _aAPPLICATIONS OF MATHEMATICS. |
| 650 | 2 | 4 | _aOPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING. |
| 650 | 2 | 4 | _aBIOMEDICAL ENGINEERING. |
| 650 | 2 | 4 | _aSTATISTICS FOR LIFE SCIENCES, MEDICINE, HEALTH SCIENCES. |
| 700 | 1 |
_aBoginski, Vladimir L. _eeditor. |
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| 700 | 1 |
_aVazacopoulos, Alkis. _eeditor. |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9780387693187 |
| 830 | 0 |
_aSpringer Optimization and Its Applications, _x1931-6828 ; _v7 |
|
| 856 | 4 | 0 |
_uhttp://dx.doi.org/10.1007/978-0-387-69319-4 _zVer el texto completo en las instalaciones del CICY |
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