Wireless Mobile Communication and Healthcare. Third International Conference, MobiHealth 2012, Paris, France, November 21-23, 2012, Revised Selected Papers

Research Article

Data Processing from mHealth Patient Data Acquisition Related to Extracting Structured Data from EH Records

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  • @INPROCEEDINGS{10.1007/978-3-642-37893-5_29,
        author={Stefan Balogh and Fedor Lehocki and Daniel Ivaniš and Erik Kučera and Miloš Lajtman and Igor Miňo},
        title={Data Processing from mHealth Patient Data Acquisition Related to Extracting Structured Data from EH Records},
        proceedings={Wireless Mobile Communication and Healthcare. Third International Conference, MobiHealth 2012, Paris, France, November 21-23, 2012, Revised Selected Papers},
        proceedings_a={MOBIHEALTH},
        year={2013},
        month={4},
        keywords={Natural language processing NLP health reports structured data telemedicine},
        doi={10.1007/978-3-642-37893-5_29}
    }
    
  • Stefan Balogh
    Fedor Lehocki
    Daniel Ivaniš
    Erik Kučera
    Miloš Lajtman
    Igor Miňo
    Year: 2013
    Data Processing from mHealth Patient Data Acquisition Related to Extracting Structured Data from EH Records
    MOBIHEALTH
    Springer
    DOI: 10.1007/978-3-642-37893-5_29
Stefan Balogh1,*, Fedor Lehocki1,*, Daniel Ivaniš1,*, Erik Kučera1,*, Miloš Lajtman1,*, Igor Miňo1,*
  • 1: Slovak University of Technology
*Contact email: stefan.balogh@stuba.sk, fedor.lehocki@stuba.sk, daniel.ivanis@stuba.sk, erik.kucera@stuba.sk, milos.lajtman@stuba.sk, igor.mino@stuba.sk

Abstract

Application of mobile devices in healthcare is a pervasive way how to asses patient health status. Adding just another data source to overwhelmed physician requires technologies for their effective processing. Despite the fact that the problem of extracting clinical information from free-text health reports for computerized applications or for decision support systems is a lot discussed issue, it is still complicated and unresolved question. In general Natural language processing (NLP) systems are implemented to solve the task. However NLP system works only for relatively narrow clinical domains because the format of the language used in the reports is not standardized and the reports vary depending on the domain. We describe methodology suggested for extracting structured data from EHR focusing especially on EHR in Slovak language. Further, we discuss problems concerning a task of extracting required data from free-text health reports. In the conclusion we present test results and possible implementations.