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Data Analysis and Data Mining: Current Issues in Biomedical Informatics

Journal: Methods of Information in Medicine
Subtitle: A journal stressing, for more than 50 years, the methodology and scientific fundamentals of organizing, representing and analyzing data, information and knowledge in biomedicine and health care
ISSN: 0026-1270
DOI: http://dx.doi.org/10.3414/ME11-06-0002
Issue: 2011 (Vol. 50): Issue 6 2011
Pages: 536-544
Ahead of Print: ###MANUSCRIPT_aheadofprint###

Data Analysis and Data Mining: Current Issues in Biomedical Informatics

R. Bellazzi (1), M. Diomidous (2), I. N. Sarkar (3), K. Takabayashi (4), A. Ziegler (5), A. T. McCray (6)

(1) Dipartimento di Informatica e Sistemistica, University of Pavia, Pavia, Italy; (2) Department of Public Health, Faculty of Nursing, University of Athens, Athens, Greece; (3) Center for Clinical and Translational Science, Department of Microbiology and Molecular Genetics, and Department of Computer Science, University of Vermont, Burlington, VT, USA; (4) Division of Medical Informatics and Management, Chiba University Hospital, Chiba, Japan; (5) Institut für Medizinische Biometrie und Statistik, University of Luebeck, Luebeck, Germany; (6) Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA

Keywords

Data Mining, biomedical informatics, data analysis, Translational bioinformatics, data-driven methods

Summary

Background: Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. Objectives: To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods: On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, which reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. Results: The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. Conclusions: Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers.

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