Data Mining in Biomedicine

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Pardalos, Panos M. (Επιμελητής έκδοσης), Boginski, Vladimir L. (Επιμελητής έκδοσης), Vazacopoulos, Alkis (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston, MA : Springer US, 2007.
• Σειρά: Springer Optimization and Its Applications, 7
• Θέματα: Medicine.; Applied mathematics.; Engineering mathematics.; Operations research.; Management science.; Statistics.; Biomedical engineering.; Biomedicine.; Biomedicine general.; Applications of Mathematics.; Operations Research, Management Science.; Biomedical Engineering.; Statistics for Life Sciences, Medicine, Health Sciences.

 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.