Biomedical Data Mining

N. Peek; C. Combi; A. Tucker

doi:10.1055/s-0038-1625129

Methods of Information in Medicine, Inhaltsverzeichnis

Methods Inf Med 2009; 48(03): 225-228
DOI: 10.1055/s-0038-1625129

Editorial

Schattauer GmbH

Biomedical Data Mining

N. Peek

¹Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

,

C. Combi

²Department of Computer Science, University of Verona, Verona, Italy

,

A. Tucker

³School of Information Systems, Computing and Mathematics, Brunel, London, UK

› Institutsangaben

Abstract

Summary

Objective: To introduce the special topic of Methods of Information in Medicine on data mining in biomedicine, with selected papers from two workshops on Intelligent Data Analysis in bioMedicine (IDAMAP) held in Verona (2006) and Amsterdam (2007).

Methods: Defining the field of biomedical data mining. Characterizing current developments and challenges for researchers in the field. Reporting on current and future activities of IMIA’s working group on Intelligent Data Analysis and Data Mining. Describing the content of the selected papers in this special topic.

Results and Conclusions: In the biomedical field, data mining methods are used to develop clinical diagnostic and prognostic systems, to interpret biomedical signal and image data, to discover knowledge from biological and clinical databases, and in biosurveillance and anomaly detection applications. The main challenges for the field are i) dealing with very large search spaces in a both computationally efficient and statistically valid manner, ii) incorporating and utilizing medical and biological background knowledge in the data analysis process, iii) reasoning with time-oriented data and temporal abstraction, and iv) developing end-user tools for interactive presentation, interpretation, and analysis of large datasets.

Keywords

Data mining - machine learning

Volltext

Referenzen

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