Open Source Infrastructure for Health Care Data Integration and Machine Learning Analyses.

Journal: JCO clinical cancer informatics
Published Date: Aug 1, 2019

Abstract

PURPOSE: We have created a cloud-based machine learning system (CLOBNET) that is an open-source, lean infrastructure for electronic health record (EHR) data integration and is capable of extract, transform, and load (ETL) processing. CLOBNET enables comprehensive analysis and visualization of structured EHR data. We demonstrate the utility of CLOBNET by predicting primary therapy outcomes of patients with high-grade serous ovarian cancer (HGSOC) on the basis of EHR data.

Authors

  • Veli-Matti Isoviita
    Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.
  • Liina Salminen
    Turku University Hospital, Turku, Finland.
  • Jimmy Azar
    Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.
  • Rainer Lehtonen
    Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.
  • Pia Roering
    University of Turku, Turku, Finland.
  • Olli Carpén
    Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.
  • Sakari Hietanen
    Turku University Hospital, Turku, Finland.
  • Seija Grénman
    Turku University Hospital, Turku, Finland.
  • Johanna Hynninen
    Turku University Hospital, Turku, Finland.
  • Anniina Färkkilä
    Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.
  • Sampsa Hautaniemi
    Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.

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