Optimization and Data Analysis in Biomedical Informatics (eBook, PDF)

• Format: PDF

Produktbeschreibung

This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11-12, 2010 a workshop entitled ‘Optimization and Data Analysis in Biomedical Informatics’ was organized at The Fields Institute. Following this event invited contributions were gathered based on the talks presented at the workshop, and additional invited chapters were chosen from world’s leading experts. In this publication, the authors share their expertise in the form of state-of-the-art research and review chapters, bringing together researchers from different disciplines and emphasizing the value of mathematical methods in the areas of clinical sciences. This work is targeted to applied mathematicians, computer scientists, industrial engineers, and clinical scientists who are interested in exploring emerging and fascinating interdisciplinary topics of research. It is designed to further stimulate and enhance fruitful collaborations between scientists from different disciplines.

Produktdetails

• Verlag: Springer New York / The Fields Institute for Research in Mathematical Sciences
• Erscheinungstermin: 15. August 2012
• Englisch
• ISBN-13: 9781461441335
• Artikelnr.: 37794574

Inhaltsangabe

Preface.- Novel Biclustering Methods for Re-Ordering Data Matrices (P.A. DiMaggio Jr., A. Subramani, C.A. Floudas).- Clustering Time Series Data with Distance Matrices (O. Şeref, W.A. Chaovalitwongse).- Mathematical Models of Supervised Learning and Application to Medical Diagnosis (R. De Asmundis, M.R. Guarracino).- Predictive Model for Early Detection of Mild Cognitive Impairment and Alzheimer’s Disease (E.K. Lee, T.-L. Wu, F. Goldstein, A. Levey).- Strategies for Bias Reduction in Estimation of Marginal Means with Data Missing at Random (B. Chen, R.J. Cook).- Cardiovascular Informatics: A Perspective on Promises and Challenges of IVUS Data Analysis (I.A. Kakadiaris, E.G.M. Ruiz).- An Introduction to the Analysis of Functional Magnetic Resonance Imaging Data (G. Gazzola, C.-A. Chou, M.K. Jeong, W.A. Chaovalitwongse).- Sensory Neuroprostheses: From Signal Processing and Coding to Neural Plasticity in the Central Nervous System (F. Panetsos, A. Sanchez-Jimenez, C. Herrera-Rincon).- EEG Based Biomarker Identification Using Graph-Theoretic Concepts: Case Study in Alcoholism (V. Sakkalis, K. Marias).- Maximal Connectivity and Constraints in the Human Brain (R.V. Belavkin).

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Preface.- Novel Biclustering Methods for Re-Ordering DataMatrices (P.A. DiMaggio Jr., A. Subramani, C.A. Floudas).- Clustering TimeSeries Data with Distance Matrices (O. Seref, W.A. Chaovalitwongse).- Mathematical Models of SupervisedLearning and Application to Medical Diagnosis (R. De Asmundis, M.R.Guarracino).- Predictive Model for Early Detection of Mild Cognitive Impairmentand Alzheimer's Disease (E.K. Lee, T.-L. Wu, F. Goldstein, A. Levey).-Strategies for Bias Reduction in Estimation of Marginal Means with Data Missingat Random (B. Chen, R.J. Cook).- Cardiovascular Informatics: A Perspective onPromises and Challenges of IVUS Data Analysis (I.A. Kakadiaris, E.G.M. Ruiz).-An Introduction to the Analysis of Functional Magnetic Resonance Imaging Data(G. Gazzola, C.-A. Chou, M.K. Jeong, W.A. Chaovalitwongse).- SensoryNeuroprostheses: From Signal Processing and Coding to Neural Plasticity in theCentral Nervous System (F. Panetsos, A. Sanchez-Jimenez, C. Herrera-Rincon).-EEG Based Biomarker Identification Using Graph-Theoretic Concepts: Case Studyin Alcoholism (V. Sakkalis, K. Marias).- Maximal Connectivity and Constraintsin the Human Brain (R.V. Belavkin).

Rezensionen

From the reviews:

"This collection of chapters in the field of bioinformatics focuses on quantitative analysis. A number of examples accompany the methodology, so readers can easily understand how to apply the methods to solve problems. ... this book provides a comprehensive introduction to the quantitative analysis of biomedical data. It is a great handbook for beginners entering the field of bioinformatics." (Hsun-Hsien Chang, ACM Computing Reviews, January, 2013)