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This book constitutes the refereed proceedings of the 4th International Symposium on Medical Data Analysis, ISMDA 2003, held in Berlin, Germany in October 2003. The 15 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on medical models and learning, integration of intelligent analysis methods into medical databases, medical signal processing and image analysis, and applications of medical diagnostic support systems.
It is a pleasure for us to present the contributions of the First International Symposium on Medical Data Analysis. Traditionally, the eld of medical data analysis can be devided into classical topics such as medical statistics, sur- val analysis, biometrics and medical informatics. Recently, however, time series analysis by physicists, machine learning and data mining with methods such as neural networks, Bayes networks or fuzzy computing by computer scientists have contributed important ideas to the led of medical data analysis. Although all these groups have similar intentions, there was nearly no exchange or discussion between them. With the growing possibilities for storing and ana- zin...
This book constitutes the refereed proceedings of the 7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006, held in Thessaloniki, Greece, December 2006. Coverage in this volume includes functional genomics, sequence analysis, biomedical models, information modeling, biomedical signal processing, biomedical image analysis, biomedical data analysis, as well as decision support systems and diagnostic tools.
Neural network and artificial intelligence algorithrns and computing have increased not only in complexity but also in the number of applications. This in turn has posed a tremendous need for a larger computational power that conventional scalar processors may not be able to deliver efficiently. These processors are oriented towards numeric and data manipulations. Due to the neurocomputing requirements (such as non-programming and learning) and the artificial intelligence requirements (such as symbolic manipulation and knowledge representation) a different set of constraints and demands are imposed on the computer architectures/organizations for these applications. Research and development o...
The 2nd International Symposium on Medical Data Analysis (ISMDA 2001) was the continuation of the successful ISMDA 2000, a conference held in Fra- furt, Germany, in September 2000. The ISMDA conferences were conceived to integrate interdisciplinary research from scienti?c ?elds such as statistics, s- nal processing, medical informatics, data mining, and biometrics for biomedical data analysis. A number of academic and professional people from those ?elds, including computer scientists, statisticians, physicians, engineers, and others, - alized that new approaches were needed to apply successfully all the traditional techniques, methods, and tools of data analysis to medicine. ISMDA 2001, as ...
Thisyear,the5thInternationalSymposiumonMedicalDataAnalysishasexperimented an apparently slight modi?cation. The word "biological" has been added to the title of the conferences. The motivation for this shift goes beyond the wish to attract a diff- ent kind of professional. It is linked to recent trends to produce a shift within various biomedical areas towards genomics-based research and practice. For instance, medical informaticsandbioinformaticsarebeinglinkedina synergicareadenominatedbiom- ical informatics.Similarly,patient careis beingimproved,leadingto conceptsandareas such as molecular medicine, genomic medicine or personalized healthcare. The resultsfromdifferentgenomeprojects,the adv...
Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation st...
This book develops a model to evaluate and assess life-cycle greenhouse gas emissions based on typical Australian commercial building design options. It also draws comparisons between some of the many green building rating tools that have been developed worldwide to support sustainable development. These include: Leadership in Energy and Environmental Design (LEED) by the United States Green Building Council (USGBC), Building Research Establishment Environmental Assessment Method (BREEAM) by the Building Research Establishment, Comprehensive Assessment System for Building Environmental Efficiency (CASBEE) by the Japanese Sustainable Building Consortium, and Green Star Environmental Rating Sy...