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Audiovisual . 2025
License: CC BY
Data sources: ZENODO
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Audiovisual . 2025
License: CC BY
Data sources: Datacite
ZENODO
Audiovisual . 2025
License: CC BY
Data sources: Datacite
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MJFF Data Community Webinar: Digital Phenotyping with PDkit - Open Source Software for Analysis of Wearables and Mobile App Data

Authors: Roussos, George;

MJFF Data Community Webinar: Digital Phenotyping with PDkit - Open Source Software for Analysis of Wearables and Mobile App Data

Abstract

In this webinar, Dr. George Roussos (Birkbeck College, University of London) gives an overview of PDkit, a Python-based open source data science toolkit to support data-driven systems using smartphones and wearables. Developed by Dr. Roussos’ team and supported by the Michael J. Fox Foundation, PDkit leverages wearables and mobile app data to support longitudinal investigations of disease mechanisms and progression. PDkit serves as an open source and scalable toolkit for high-frequency assessment of PD symptoms. To learn more about PDkit, you can also read Dr Roussos' post on our community platform. This webinar was organized by the the Michael J. Fox Foundation's Data Community of Practice (DCoP). Do you have ideas or suggestions for other webinar topics you would like to see? Is there a tool you feel the community would benefit from highlighting? Let us know by leaving your thoughts in this thread: Seeking Webinar Ideas and Requests from the Community, or by contacting researchcommunity@michaeljfox.org. For those interested in joining or contributing to the DCoP, please visit rcop.michaeljfox.org. 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average