Ontology-Guided Principal Component Analysis: Reaching the limits of the doctor-in-the-loop

Sandra Wartner; Dominic Girardi; Johannes Trenkler; Manuela Wiesinger-Widi; Raimund Kleiser; Andreas Holzinger

doi:10.1007/978-3-319-43949-5_2

Ontology-Guided Principal Component Analysis: Reaching the limits of the doctor-in-the-loop

Sandra Wartner, Dominic Girardi, Johannes Trenkler, Manuela Wiesinger-Widi, Raimund Kleiser, Andreas Holzinger

Institute of Interactive Systems and Data Science (7060)

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Biomedical research requires deep domain expertise to perform analyses of complex data sets, assisted by mathematical expertise
provided by data scientists who design and develop sophisticated methods and tools. Such methods and tools not only require preprocessing
of the data, but most of all a meaningful input selection. Usually, data
scientists do not have sufficient background knowledge about the origin
of the data and the biomedical problems to be solved, consequently a
doctor-in-the-loop can be of great help here. In this paper we revise the
viability of integrating an analysis guided visualization component in an
ontology-guided data infrastructure, exemplified by the principal component analysis. We evaluated this approach by examining the potential for
intelligent support of medical experts on the case of cerebral aneurysms
research.

Original language	English
Title of host publication	Springer Lecture Notes in Computer Science LNCS 9832
Subtitle of host publication	Information Technology in Bio- and Medical Informatics
Place of Publication	Heidelberg, Berlin, New York
Publisher	Springer
Pages	22-33
DOIs	https://doi.org/10.1007/978-3-319-43949-5_2
Publication status	Published - 19 Aug 2016

Keywords

health informatics
Machine Learning
Doctor-in-the-loop

ASJC Scopus subject areas

Artificial Intelligence

Fields of Expertise

Information, Communication & Computing

Treatment code (Nähere Zuordnung)

Basic - Fundamental (Grundlagenforschung)

Access to Document

10.1007/978-3-319-43949-5_2

Doctor-in-the-loop-reaching-limitsFinal published version, 558 KBLicence: CC BY 4.0

Cite this

Ontology-Guided Principal Component Analysis: Reaching the limits of the doctor-in-the-loop. / Wartner, Sandra; Girardi, Dominic; Trenkler, Johannes et al.
Springer Lecture Notes in Computer Science LNCS 9832: Information Technology in Bio- and Medical Informatics. Heidelberg, Berlin, New York: Springer, 2016. p. 22-33.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Wartner, S, Girardi, D, Trenkler, J, Wiesinger-Widi, M, Kleiser, R & Holzinger, A 2016, Ontology-Guided Principal Component Analysis: Reaching the limits of the doctor-in-the-loop. in Springer Lecture Notes in Computer Science LNCS 9832: Information Technology in Bio- and Medical Informatics. Springer, Heidelberg, Berlin, New York, pp. 22-33. https://doi.org/10.1007/978-3-319-43949-5_2

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AU - Holzinger, Andreas

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AB - Biomedical research requires deep domain expertise to perform analyses of complex data sets, assisted by mathematical expertiseprovided by data scientists who design and develop sophisticated methods and tools. Such methods and tools not only require preprocessingof the data, but most of all a meaningful input selection. Usually, datascientists do not have sufficient background knowledge about the originof the data and the biomedical problems to be solved, consequently adoctor-in-the-loop can be of great help here. In this paper we revise theviability of integrating an analysis guided visualization component in anontology-guided data infrastructure, exemplified by the principal component analysis. We evaluated this approach by examining the potential forintelligent support of medical experts on the case of cerebral aneurysmsresearch.

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Ontology-Guided Principal Component Analysis: Reaching the limits of the doctor-in-the-loop

Abstract

Keywords

ASJC Scopus subject areas

Fields of Expertise

Treatment code (Nähere Zuordnung)

Access to Document

Fingerprint

Cite this