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Towards Understanding ICU Treatments Using Patient Health Trajectories

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Book cover Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems (KR4HC 2019, TEAAM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11979))

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Abstract

Overtreatment or mistreatment of patients is a phenomenon commonly encountered in health care and especially in the Intensive Care Unit (ICU) resulting in increased morbidity and mortality. We explore the MIMIC-III intensive care unit database and conduct experiments on an interpretable feature space based on the fusion of severity subscores, commonly used to predict mortality in an ICU setting. Clustering of medication and procedure context vectors based on a semantic representation has been performed to find common and individual treatment patterns. Two-day patient health state trajectories of a cohort of congestive heart failure patients are clustered and correlated with the treatment and evaluated based on an increase or reduction of probability of mortality on the second day of stay. Experimental results show differences in treatments and outcomes and the potential for using patient health state trajectories as a starting point for further evaluation of medical treatments and interventions.

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Notes

  1. 1.

    https://github.com/MIT-LCP/mimic-code.

  2. 2.

    https://github.com/caisr-hh/Dayly-SAPS-III-and-OASIS-scores-for-MIMIC-III.

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Authors and Affiliations

  1. Center for Applied Intelligent Systems Research, Halmstad University, Kristian IV:s väg 3, 301 18, Halmstad, Sweden

    Alexander Galozy, Sławomir Nowaczyk & Anita Sant’Anna

Authors
  1. Alexander Galozy
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  2. Sławomir Nowaczyk
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  3. Anita Sant’Anna
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Corresponding author

Correspondence to Alexander Galozy .

Editor information

Editors and Affiliations

  1. Universitat Jaume I, Castellón, Spain

    Mar Marcos

  2. University of Murcia, Murcia, Spain

    Jose M. Juarez

  3. Friedrich-Alexander-University of Erlangen-Nuremberg, Erlangen, Germany

    Richard Lenz

  4. Jagiellonian University and AGH University of Science and Technology, Kraków, Poland

    Grzegorz J. Nalepa

  5. Halmstad University, Halmstad, Sweden

    Slawomir Nowaczyk

  6. University of Haifa, Haifa, Israel

    Mor Peleg

  7. Poznań University of Technology, Poznan, Poland

    Jerzy Stefanowski

  8. University of Maribor, Maribor, Slovenia

    Gregor Stiglic

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Galozy, A., Nowaczyk, S., Sant’Anna, A. (2019). Towards Understanding ICU Treatments Using Patient Health Trajectories. In: Marcos, M., et al. Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems. KR4HC TEAAM 2019 2019. Lecture Notes in Computer Science(), vol 11979. Springer, Cham. https://doi.org/10.1007/978-3-030-37446-4_6

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  • DOI: https://doi.org/10.1007/978-3-030-37446-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37445-7

  • Online ISBN: 978-3-030-37446-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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