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Data Mining in Biomedicine: Springer Optimization and Its Applications, cartea 7

Editat de Panos M. Pardalos, Vladimir L. Boginski, Alkis Vazacopoulos
en Limba Engleză Paperback – 19 noi 2010

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Specificații

ISBN-13: 9781441943439
ISBN-10: 1441943439
Pagini: 600
Ilustrații: XVII, 582 p.
Dimensiuni: 155 x 235 x 32 mm
Greutate: 0.83 kg
Ediția:Softcover reprint of hardcover 1st ed. 2007
Editura: Springer Us
Colecția Springer
Seria Springer Optimization and Its Applications

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

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.

Recenzii

From the reviews:
"This book is an in-depth look at ‘the development of appropriate methods for extracting useful information’ from data in biomedicine. … is aimed at scientists and practitioners in the fields of biomedicine, engineering, mathematics, and computer science as well as graduate students and is appropriate for a variety of readers. … A well compiled volume on the application of data mining to biomedicine, this book will be a welcome addition to the literature." (Nicole Mitchell, Doody’s Review Service, August, 2008)

Caracteristici

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