Integrating gait sensor data with other multimodal datasets to predict PD outcomes

GLAAB, Enrico

Scientific presentation in universities or research centers (Scientific presentations in universities or research centers)

GLAAB, Enrico

2024

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https://hdl.handle.net/10993/62539

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Keywords :

Parkinson's disease; biomarker; digital; gait; machine learning; statistics

Research center :

Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group)

Disciplines :

Neurology
Biotechnology
Life sciences: Multidisciplinary, general & others
Human health sciences: Multidisciplinary, general & others

Author, co-author :

GLAAB, Enrico ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Biomedical Data Science

Language :

English

Title :

Integrating gait sensor data with other multimodal datasets to predict PD outcomes

Publication date :

2024

Event name :

Symposium „Validating DIGItal biomarkers for better personalized treatment of Parkinson's Disease“

Event organizer :

Fraunhofer Institute for Algorithms and Scientific Computing (SCAI)

Event place :

Bonn, Germany

Event date :

15-04-2024

Audience :

International

Focus Area :

Systems Biomedicine

Development Goals :

3. Good health and well-being

FnR Project :

R-AGR-3931 - INTER/ERAPerMed 20/14599012/DIGIPD

Name of the research project :

R-AGR-3931 - INTER/ERAPerMed 20/14599012/DIGIPD - GLAAB Enrico

Funders :

FNR - Fonds National de la Recherche

Funding number :

INTER/ERAPerMed 20/14599012/DIGIPD

Available on ORBilu :

since 15 November 2024

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