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Information Systems Frontiers
Erschienen in: Information Systems Frontiers 4/2009

01.09.2009

Interactive survival analysis with the OCDM system: From development to application

verfasst von: Sebastian Klenk, Jürgen Dippon, Peter Fritz, Gunther Heidemann

Erschienen in: Information Systems Frontiers | Ausgabe 4/2009

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Abstract

Medical data mining is currently actively pursued in computer science and statistical research but not in medical practice. The reasons therefore lie in the difficulties of handling and statistically analyzing medical data. We have developed a system that allows practitioners in the field to interactively analyze their data without assistance of statisticians or data mining experts. In the course of this paper we will introduce data mining of medical data and show how this can be achieved for survival data. We will demonstrate how to solve common problems of interactive survival analysis by presenting the Online Clinical Data Mining (OCDM) system. Thereby the main focus is on similarity based queries, a new method to select similar cases based on their covariables and the influence of these on their survival.
Vorheriger Artikel Image fusion enhancement of deformable human structures using a two-stage warping-deformable strategy: A content-based image retrieval consideration
Nächster Artikel Design of an RFID-based Healthcare Management System using an Information System Design Theory

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Fußnoten
1
OnLine Analytical Processing—A hypothesis driven, dimensional approach to decision support (Kimball 1996).
 
2
The terms knowledge discovery in databases (KDD) and data mining (DM) are used in accordance with Fayyad et al. (1996). When it comes to actual software systems we will use the terms data mining or knowledge discovery system variantly.
 
3
In this paper we use the term data warehouse in a broader sense, as a storage system for a large number of information from different sources.
 
4
A non-parametric method to estimate the conditional expectation of a random variable Y, given the value x of its covariate, by a locally weighted average of the observations Y i related to the vicinity of x which is moderated by a kernel function and a bandwidth, see Hastie et al. (2002), e.g.
 
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Metadaten
Titel
Interactive survival analysis with the OCDM system: From development to application
verfasst von
Sebastian Klenk
Jürgen Dippon
Peter Fritz
Gunther Heidemann
Publikationsdatum
01.09.2009
Verlag
Springer US
Erschienen in
Information Systems Frontiers / Ausgabe 4/2009
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-009-9152-5

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EditorialNotes

Editorial for the special issue of knowledge discovery and management in biomedical information systems