Sebanyak 5 item atau buku ditemukan

Data Mining, Systems Analysis, and Optimization in Biomedicine

This book is a collection of a sample of the latest research methods in data mining across diverse fields of biomedicine, neuroscience, engineering, and computer science. The problems and methods discussed in this book will be of great interest to new and established theoreticians and practitioners in these fields and provide them with new directions for research. The book will be required reading for biomedical and industrial engineers, computer scientists, and medical doctors.

This book is a collection of a sample of the latest research methods in data mining across diverse fields of biomedicine, neuroscience, engineering, and computer science.

Data Mining and Mathematical Programming

Data mining aims at finding interesting, useful or profitable information in very large databases. The enormous increase in the size of available scientific and commercial databases (data avalanche) as well as the continuing and exponential growth in performance of present day computers make data mining a very active field. In many cases, the burgeoning volume of data sets has grown so large that it threatens to overwhelm rather than enlighten scientists. Therefore, traditional methods are revised and streamlined, complemented by many new methods to address challenging new problems. Mathematical Programming plays a key role in this endeavor. It helps us to formulate precise objectives (e.g., a clustering criterion or a measure of discrimination) as well as the constraints imposed on the solution (e.g., find a partition, a covering or a hierarchy in clustering). It also provides powerful mathematical tools to build highly performing exact or approximate algorithms. This book is based on lectures presented at the workshop on "Data Mining and Mathematical Programming" (October 10-13, 2006, Montreal) and will be a valuable scientific source of information to faculty, students, and researchers in optimization, data analysis and data mining, as well as people working in computer science, engineering and applied mathematics.

This chapter is focused on recent advances in mathematical programming
methodologies in data mining research, which is a rapidly emerging
interdisciplinary research area. The main focus of this review chapter lies on
classification ...

Data Mining in Agriculture

Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLAB®.

This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLAB®.

Data Mining in Biomedicine

This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.

Mining. in. EEG: Application. to. Epileptic. Brain. Disorders*. P.M. Pardalos2, L.D.
Iasemidis3 , W. Suharitdamrong2, D.-S. Shiau2, L.K. Dance2, O.A. Prokopyev4,
V.L. Boginski5, PR. Carney2, and J.C. Sackellares2 1 Rutgers University, USA ...

Data Mining for Biomarker Discovery

Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques. This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.

This volume is a collection of state-of-the-art research from select participants of the “International Conference on Biomedical Data and Knowledge Mining: Towards Biomarker Discovery,” held July 7-9, 2010 in Chania, Greece.