Analysis of Patient Groups and Immunization Results Based on Subspace Clustering

Abstract

Biomedical experts are increasingly confronted with what is often called Big Data, an important subclass of high-dimensional data. High-dimensional data analysis can be helpful in finding relationships between records and dimensions. However, due to data complexity, experts are decreasingly capable of dealing with increasingly complex data. Mapping higher… (More)
DOI: 10.1007/978-3-319-23344-4_35

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@inproceedings{Hund2015AnalysisOP, title={Analysis of Patient Groups and Immunization Results Based on Subspace Clustering}, author={Michael Hund and Werner Sturm and Tobias Schreck and Torsten Ullrich and Daniel A. Keim and Ljiljana Majnaric and Andreas Holzinger}, booktitle={BIH}, year={2015} }