Optimization and Data Analysis in Biomedical Informatics

1. Front Matter

   Pages i-viii

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2. Novel Biclustering Methods for Re-ordering Data Matrices

   • Peter A. DiMaggio Jr., Ashwin Subramani, Christodoulos A. Floudas

   Pages 1-39

3. Clustering Time Series Data with Distance Matrices

   • Onur Şeref, W. Art Chaovalitwongse

   Pages 41-66

4. Mathematical Models of Supervised Learning and Application to Medical Diagnosis

   • Roberta De Asmundis, Mario Rosario Guarracino

   Pages 67-81

5. Predictive Model for Early Detection of Mild Cognitive Impairment and Alzheimer’s Disease

   • Eva K. Lee, Tsung-Lin Wu, Felicia Goldstein, Allan Levey

   Pages 83-97

6. Strategies for Bias Reduction in Estimation of Marginal Means with Data Missing at Random

   • Baojiang Chen, Richard J. Cook

   Pages 99-115

7. Cardiovascular Informatics: A Perspective on Promises and Challenges of IVUS Data Analysis

   • Ioannis A. Kakadiaris, E. Gerardo Mendizabal Ruiz

   Pages 117-130

8. An Introduction to the Analysis of Functional Magnetic Resonance Imaging Data

   • Gianluca Gazzola, Chun-An Chou, Myong K. Jeong, W. Art Chaovalitwongse

   Pages 131-151

9. Sensory Neuroprostheses: From Signal Processing and Coding to Neural Plasticity in the Central Nervous System

   • Fivos Panetsos, Abel Sanchez-Jimenez, Celia Herrera-Rincon

   Pages 153-169

10. EEG Based Biomarker Identification Using Graph-Theoretic Concepts: Case Study in Alcoholism

    • Vangelis Sakkalis, Konstantinos Marias

    Pages 171-189

11. Maximal Connectivity and Constraints in the Human Brain

    • Roman V. Belavkin

    Pages 191-198

​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.​

• Cardiovascular Informatics
• Mathematical Models of medical diagnosis
• Predictive Model for Early Detection of Alzheimer’s Disease
• bioinformatics
• data analysis in biomedical informatics
• optimization in biomedical informatics
• biochemical engineering

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)

• , Department of Industrial & Systems Engin, University of Florida, Gainesville, USA

  Panos M. Pardalos

• , Department of Mathematics, University of Waterloo, Waterloo, Canada

  Thomas F. Coleman

• , Department of Industrial Engineering, University of Central Florida, Orlando, USA

  Petros Xanthopoulos

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