"Data mining has rapidly emerged as an enabling, robust, and scalable technique to analyze data for novel patterns, trends, anomalies, structures, and features that can be employed for a variety of biomedical and clinical domains. Approaching the techniques and challenges of image mining from a multidisciplinary perspective, this book presents data mining techniques, methodologies, algorithms, and strategies to analyze biomedical signals and images. Written by experts, the text addresses data mining paradigms for the development of biomedical systems. It also includes special coverage of…mehr
"Data mining has rapidly emerged as an enabling, robust, and scalable technique to analyze data for novel patterns, trends, anomalies, structures, and features that can be employed for a variety of biomedical and clinical domains. Approaching the techniques and challenges of image mining from a multidisciplinary perspective, this book presents data mining techniques, methodologies, algorithms, and strategies to analyze biomedical signals and images. Written by experts, the text addresses data mining paradigms for the development of biomedical systems. It also includes special coverage of knowledge discovery in mammograms and emphasizes both the diagnostic and therapeutic fields of eye imaging"--Provided by publisher.
Sumeet Dua, PhD, is currently an Upchurch endowed associate professor and the coordinator of IT research at Louisiana Tech University, Ruston. He also serves as adjunct faculty to the School of Medicine, Louisiana State University, Health Sciences Center in New Orleans. His areas of expertise include data mining, image processing, computational decision support, pattern recognition, data warehousing, biomedical informatics, and heterogeneous distributed data integration. The National Science Foundation (NSF), the National Institutes of Health (NIH), the Air Force Research Laboratory (AFRL), the Air Force Office of Sponsored Research, (AFOSR), and the Louisiana Board of Regents (LA-BoR) have funded his research. He frequently serves as a study section member (expert panelist) for the NIH's Center for Scientific Review and has served as a panelist for the NSF/Computing in Science in Engineering (CISE) Directorate. Dr. Dua has chaired several conference sessions in the area of data mining and bioinformatics, and is the program chair for the 5th International Conference on Information Systems, Technology, and Management (ICISTM-2011). He has given over 26 invited talks on data mining and bioinformatics at international academic and industry arenas, advised over 25 graduate theses, and currently advises several students in this field. Dr. Dua is acoinventor of two issued U.S. patents, has co-authored over 50 publications and book chapters, and is an author /editor of 4 books in data mining and bioinformatics. Dr. Dua has received the Engineering and Science Foundation Award for Faculty Excellence (2006) and the Faculty Research Recognition Award (2007); he has been recognized as a Distinguished Researcher (2004-2010) by the Louisiana Biomedical Research Network (sponsored by NIH) and has won the Oustanding Poster Award at the NIH/National Cancer Institute (NCI) caBIG-NCRI Informatics Joint Conference; Biomedical Informatics wi
Inhaltsangabe
Data Mining of Acoustical Properties of Speech as Indicators of Depression. Artificial Neural Network Based ECG Arrhythmia Classification. Human Reflexive Response and its Objective Function Regarding Balance Recovery From Perturbation During Walking. Automatic Identification of Epileptic EEG Signals Using Nonlinear Parameters. Data Mining Approach to Classify the Pathological Images in Databases Using Color Image Analysis. Discovery of Association Among Diseases in the Upper Gastro Intestinal Tract Using Data Mining Techniques. Data Analysis Techniques Applied to Metabolomics: Analysis and Classification of Migraine Patterns. System Engineering Principles in the Design of Biomedical Systems. Feature Classification Methods for Knowledge Discovery in Mammograms. Mining of Imaging Biomarkers for Quantitative Evaluation of Osteosrthritis. Typicality Measure and the Creation of Predictive Models in Biomedicine. Automatic Segmentation Methods and Applications to Biofilm Image Analysis. On Clustering Gene Expression Time-Series Signals. Multi-Scale Method For Biomedical Image Segmentation.
Data Mining of Acoustical Properties of Speech as Indicators of Depression. Artificial Neural Network Based ECG Arrhythmia Classification. Human Reflexive Response and its Objective Function Regarding Balance Recovery From Perturbation During Walking. Automatic Identification of Epileptic EEG Signals Using Nonlinear Parameters. Data Mining Approach to Classify the Pathological Images in Databases Using Color Image Analysis. Discovery of Association Among Diseases in the Upper Gastro Intestinal Tract Using Data Mining Techniques. Data Analysis Techniques Applied to Metabolomics: Analysis and Classification of Migraine Patterns. System Engineering Principles in the Design of Biomedical Systems. Feature Classification Methods for Knowledge Discovery in Mammograms. Mining of Imaging Biomarkers for Quantitative Evaluation of Osteosrthritis. Typicality Measure and the Creation of Predictive Models in Biomedicine. Automatic Segmentation Methods and Applications to Biofilm Image Analysis. On Clustering Gene Expression Time-Series Signals. Multi-Scale Method For Biomedical Image Segmentation.
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