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Data Mining in Biomedicine


Data Mining in Biomedicine


Springer Optimization and Its Applications, Band 7

von: Panos M. Pardalos, Vladimir L. Boginski, Alkis Vazacopoulos

CHF 236.00

Verlag: Springer
Format: PDF
Veröffentl.: 10.12.2008
ISBN/EAN: 9780387693194
Sprache: englisch
Anzahl Seiten: 580

Dieses eBook enthält ein Wasserzeichen.

Beschreibungen

Recent 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.
Demonstrates how new data mining methodologies are successfully applied in real-life biomedical practice, which makes it attractive to both researchers and practitioners Includes supplementary material: sn.pub/extras

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