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Journal of Intelligent Information Systems

, Volume 51, Issue 2, pp 301–337 | Cite as

Analysis of medications change in Parkinson’s disease progression data

  • Anita ValmarskaEmail author
  • Dragana Miljkovic
  • Nada Lavrač
  • Marko Robnik-Šikonja
Article

Abstract

Parkinson’s disease is a neurodegenerative disorder that affects people worldwide. Careful management of patient’s condition is crucial to ensure the patient’s independence and quality of life. This is achieved by personalized treatment based on individual patient’s symptoms and medical history. The aim of this study is to determine patient groups with similar disease progression patterns coupled with patterns of medications change that lead to the improvement or decline of patients’ quality of life symptoms. To this end, this paper proposes a new methodology for clustering of short time series of patients’ symptoms and prescribed medications data, and time sequence data analysis using skip-grams to monitor disease progression. The results demonstrate that motor and autonomic symptoms are the most informative for evaluating the quality of life of Parkinson’s disease patients. We show that Parkinson’s disease patients can be divided into clusters ordered in accordance with the severity of their symptoms. By following the evolution of symptoms for each patient separately, we were able to determine patterns of medications change which can lead to the improvement or worsening of the patients’ quality of life.

Keywords

Parkinson’s disease Quality of life indicators Clustering Short time series Skip-grams 

Notes

Acknowledgements

This work was supported by the PD_manager and HBP SGA1 projects, funded within the EU Framework Program for Research and Innovation Horizon 2020 grants 643706 and 720270, respectively. We acknowledge also the support of the Slovenian Research Agency (research core funding P2-0103 and P2-0209).

Data used in the preparation of this article were obtained from the Parkinson’s Progression Markers Initiative (PPMI) (http://www.ppmi-info.org/data). For up-to-date information on the study, visit http://www.ppmi-info.org. PPMI—a public-private partnership—is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners. Corporate Funding Partners: AbbVie, Avid Radiopharmaceuticals, Biogen, BioLegend, Bristol-Myers Squibb, GE Healthcare, GLAXOSMITHKLINE (GSK), Eli Lilly and Company, Lundbeck, Merck, Meso Scale Discovery (MSD), Pfizer Inc, Piramal Imaging, Roche, Sanofi Genzyme, Servier, Takeda, Teva, UCB. Philanthropic Funding Partners: Golub Capital. List of funding partners can be also found at http://www.ppmi-info.org/fundingpartners.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Anita Valmarska
    • 1
    • 2
    Email author
  • Dragana Miljkovic
    • 1
  • Nada Lavrač
    • 1
    • 2
    • 3
  • Marko Robnik-Šikonja
    • 4
  1. 1.Jožef Stefan InstituteLjubljanaSlovenia
  2. 2.Jožef Stefan International Postgraduate SchoolLjubljanaSlovenia
  3. 3.University of Nova GoricaNova GoricaSlovenia
  4. 4.Faculty of Computer and Information ScienceUniversity of LjubljanaLjubljanaSlovenia

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