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Machine Learning and Data Mining Methods for Managing Parkinson’s Disease

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Machine Learning for Health Informatics

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9605))

Abstract

Parkinson’s disease (PD) results primarily from dying of dopaminergic neurons in the Substantia Nigra, a part of the Mesencephalon (midbrain), which is not curable to date. PD medications treat symptoms only, none halt or retard dopaminergic neuron degeneration. Here machine learning methods can be of help since one of the crucial roles in the management and treatment of PD patients is detection and classification of tremors. In the clinical practice, this is one of the most common movement disorders and is typically classified using behavioral or etiological factors. Another important issue is to detect and evaluate PD related gait patterns, gait initiation and freezing of gait, which are typical symptoms of PD. Medical studies have shown that 90% of people with PD suffer from vocal impairment, consequently the analysis of voice data to discriminate healthy people from PD is relevant. This paper provides a quick overview of the state-of-the-art and some directions for future research, motivated by the ongoing PD_manager project.

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Notes

  1. 1.

    http://www.parkinson-manager.eu/.

  2. 2.

    Standard distance: a statistic mainly used for spatial GIS data, to measure compactness of a distribution.

  3. 3.

    https://archive.ics.uci.edu/ml/datasets/Parkinsons+Telemonitoring.

  4. 4.

    https://archive.ics.uci.edu/ml/datasets/Parkinsons.

  5. 5.

    http://www.clowdflows.org/.

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Acknowledgments

The work of the authors was supported by the PD_manager project, funded within the EU Framework Programme for Research and Innovation Horizon 2020, under grant number 643706.

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Authors and Affiliations

  1. Knowledge Technologies Department, Jožef Stefan Institute, Ljubljana, Slovenia

    Dragana Miljkovic, Darko Aleksovski, Vid Podpečan & Nada Lavrač

  2. Holzinger Group, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Graz, Austria

    Bernd Malle & Andreas Holzinger

  3. Institute of Information Systems and Computer Media, Graz University of Technology, Graz, Austria

    Andreas Holzinger

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  1. Dragana Miljkovic
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  2. Darko Aleksovski
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Correspondence to Dragana Miljkovic .

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    Andreas Holzinger

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Miljkovic, D., Aleksovski, D., Podpečan, V., Lavrač, N., Malle, B., Holzinger, A. (2016). Machine Learning and Data Mining Methods for Managing Parkinson’s Disease. In: Holzinger, A. (eds) Machine Learning for Health Informatics. Lecture Notes in Computer Science(), vol 9605. Springer, Cham. https://doi.org/10.1007/978-3-319-50478-0_10

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  • DOI: https://doi.org/10.1007/978-3-319-50478-0_10

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