Skip to main content
SpringerLink
Log in

Ontology-Guided Principal Component Analysis: Reaching the Limits of the Doctor-in-the-Loop

  • Conference paper
  • First Online:
Information Technology in Bio- and Medical Informatics (ITBAM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9832))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Akgul, C.B., Rubin, D.L., Napel, S., Beaulieu, C.F., Greenspan, H., Acar, B.: Content-based image retrieval in radiology: Current status and future directions. J. Digit. Imaging 24(2), 208–222 (2011)

    Article  Google Scholar 

  2. Anderson, N.R., Lee, E.S., Brockenbrough, J.S., Minie, M.E., Fuller, S., Brinkley, J., Tarczy-Hornoch, P.: Issues in biomedical research data management and analysis: needs and barriers. J. Am. Med. Inf. Assoc. 14(4), 478–488 (2007)

    Article  Google Scholar 

  3. Atzmüller, M., Baumeister, J., Puppe, F.: Introspective subgroup analysis for interactive knowledge refinement. In: Sutcliffe, G., Goebel, R. (eds.) FLAIRS Nineteenth International Florida Artificial Intelligence Research Society Conference, pp. 402–407. AAAI Press, Menlo Park (2006)

    Google Scholar 

  4. Buchan, I.E., Winn, J.M., Bishop, C.M.: A unified modeling approach to data-intensive healthcare. In: Hey, T., Tansley, S., Tolle, K. (eds.) The fourth paradigm: Data-Intensive Scientific Discovery, pp. 91–98. Microsoft Research, Redmond (2009)

    Google Scholar 

  5. Cios, K.J., William Moore, G.: Uniqueness of medical data mining. Artif. Intell. Med. 26(1), 1–24 (2002)

    Article  Google Scholar 

  6. Gigerenzer, G., Gaissmaier, W.: Heuristic decision making. Ann. Rev. Psychol. 62, 451–482 (2011)

    Article  Google Scholar 

  7. Girardi, D., Dirnberger, J., Giretzlehner, M.: An ontology-based clinical data warehouse for scientific research. Saf. Health 1(1), 1–9 (2015)

    Article  Google Scholar 

  8. Girardi, D., Kueng, J., Holzinger, A.: A domain-expert centered process model for knowledge discovery in medical research: putting the expert-in-the-loop. In: Guo, Y., Friston, K., Aldo, F., Hill, S., Peng, H. (eds.) BIH 2015. LNCS, vol. 9250, pp. 389–398. Springer, Heidelberg (2015)

    Chapter  Google Scholar 

  9. Girardi, D., Küng, J., Kleiser, R., Sonnberger, M., Csillag, D., Trenkler, J., Holzinger, A.: Interactive knowledge discovery with the doctor-in-the-loop: a practical example of cerebral aneurysms research. Brain Inf., 1–11 (2016). (Online First Articles)

    Google Scholar 

  10. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. ACM SIGKDD Explor. Newsl. 11(1), 10–18 (2009)

    Article  Google Scholar 

  11. Holzinger, A.: Human-computer interaction and knowledge discovery (HCI-KDD): what is the benefit of bringing those two fields to work together? In: Cuzzocrea, A., Kittl, C., Simos, D.E., Weippl, E., Xu, L. (eds.) CD-ARES 2013. LNCS, vol. 8127, pp. 319–328. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  12. Holzinger, A.: Trends in interactive knowledge discovery for personalized medicine: Cognitive science meets machine learning. IEEE Intell. Inf. Bull. 15(1), 6–14 (2014)

    Google Scholar 

  13. Holzinger, A.: Interactive machine learning for health informatics: When do we need the human-in-the-loop? Springer Brain Inform. (BRIN) 3, 1–13 (2016). http://dx.doi.org/10.1007/s40708-016-0042-6

    Article  Google Scholar 

  14. Holzinger, A., Dehmer, M., Jurisica, I.: Knowledge discovery and interactive data mining in bioinformatics - state-of-the-art, future challenges and research directions. BMC Bioinform. 15(S6), I1 (2014)

    Article  Google Scholar 

  15. Holzinger, Andreas, Stocker, Christof, Dehmer, Matthias: Big complex biomedical data: towards a taxonomy of data. In: Obaidat, Mohammad S., Filipe, Joaquim (eds.) ICETE 2012. CCIS, vol. 455, pp. 3–18. Springer, Heidelberg (2014)

    Google Scholar 

  16. Hotelling, H.: Analysis of a complex of statistical variables into principal components. J. Educ. Psychol. 24, 417–441 (1933)

    Article  MATH  Google Scholar 

  17. Hund, M., Bhm, D., Sturm, W., Sedlmair, M., Schreck, T., Ullrich, T., Keim, D.A., Majnaric, L., Holzinger, A.: Visual analytics for concept exploration in subspaces of patient groups: Making sense of complex datasets with the doctor-in-the-loop. Brain Inf. 3, 1–15 (2016)

    Article  Google Scholar 

  18. Kessler, W.: Multivariate Datenanalyse: für die Pharma-Bio- und Prozessanalytik. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim (2007)

    Google Scholar 

  19. Kurgan, L.A., Musilek, P.: A survey of knowledge discovery and data mining process models. Knowl. Eng. Rev. 21(01), 1–24 (2006)

    Article  Google Scholar 

  20. Malinowski, E.: A thesis in two parts: application of factor analysis to chemical problems. Stevens Inst. Technol. 2(1–2), 54–94 (1961)

    Google Scholar 

  21. Nandi, D., Ashour, A.S., Samanta, S., Chakraborty, S., Salem, M.A., Dey, N.: Principal component analysis in medical image processing: a study. Int. J. Image Min. 1(1), 65–86 (2015)

    Article  Google Scholar 

  22. National Center for Biotechnology Information: Mesh search for principalcomponent analysis and medicine (2016). http://www.ncbi.nlm.nih.gov/

  23. Niakšu, O., Kurasova, O.: Data mining applications in healthcare: research vs practice. Databases Inf. Syst. BalticDB&IS 2012, 58 (2012)

    Google Scholar 

  24. NIH: Cerebral Aneurysm Information Page (April 2010). http://www.ninds.nih.gov/disorders/cerebral_aneurysm/cerebral_aneurysm.htm

  25. Pearson, K.: On lines and planes of closest fit to systems of points in space. Philos. Mag. 2, 559–572 (1901)

    Article  MATH  Google Scholar 

  26. Rencher, A.: Methods of Multivariate Analysis. Wiley Series in Probability and Statistics. Wiley, Chichester (2002)

    Book  MATH  Google Scholar 

  27. Sharaf, M., Illman, D., Kowalski, B.: Chemometrics. Wiley, New York (1986)

    Google Scholar 

  28. Thurstone, L.: Multiple-factor Analysis: A Development and Expansion of The Vectors of Mind. The university of Chicago committee on publications in biology and medicine. University of Chicago Press, New York (1947)

    MATH  Google Scholar 

  29. Thurstone, L., Thurston, T.: Factorial Studies of Intelligence. Psychometrika monograph suplements. The University of Chicago press, Chicago (1941)

    Google Scholar 

  30. Wang, B.B., Mckay, R.I., Abbass, H.A., Barlow, M.: A comparative study for domain ontology guided feature extraction. In: Proceedings of the 26th Australasian Computer Science Conference vol. 16, pp. 69–78. Australian Computer Society, Inc. (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research Unit Medical Informatics at RISC Software GmbH, Johannes Kepler University, Hagenberg and Linz, Austria

    Sandra Wartner, Dominic Girardi & Manuela Wiesinger-Widi

  2. Institute of Neuroradiology at Neuromed Campus of the Kepler University Klinikum, Linz, Austria

    Johannes Trenkler & Raimund Kleiser

  3. Research Unit, HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Graz, Austria

    Andreas Holzinger

Authors
  1. Sandra Wartner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dominic Girardi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Manuela Wiesinger-Widi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Johannes Trenkler
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Raimund Kleiser
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Andreas Holzinger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dominic Girardi .

Editor information

Editors and Affiliations

  1. Institute of Informatics and Telematics , Pisa, Italy

    M. Elena Renda

  2. Czech Technical University in Prague , Prague 6, Czech Republic

    Miroslav Bursa

  3. Medical University Graz , Graz, Austria

    Andreas Holzinger

  4. San José State University , San Jose, California, USA

    Sami Khuri

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Wartner, S., Girardi, D., Wiesinger-Widi, M., Trenkler, J., Kleiser, R., Holzinger, A. (2016). Ontology-Guided Principal Component Analysis: Reaching the Limits of the Doctor-in-the-Loop. In: Renda, M., Bursa, M., Holzinger, A., Khuri, S. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2016. Lecture Notes in Computer Science(), vol 9832. Springer, Cham. https://doi.org/10.1007/978-3-319-43949-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-43949-5_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43948-8

  • Online ISBN: 978-3-319-43949-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation