Integrative machine learning analysis of digital biomarkers, clinical, and omics data for Parkinson's disease

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/10993/62540

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Keywords :

Parkinson's disease; digital biomarkers; gait; machine learning; prediction; omics; clinical data

Research center :

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

Disciplines :

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

Author, co-author :

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

Language :

English

Title :

Integrative machine learning analysis of digital biomarkers, clinical, and omics data for Parkinson's disease

Publication date :

2024

Event name :

DIGIPD General Assembly Meeting

Event organizer :

University of Luxembourg

Event place :

Luxembourg

Event date :

19-06-2023

Audience :

International

Focus Area :

Systems Biomedicine

Development Goals :

3. Good health and well-being

FnR Project :

FNR14599012 - Validating Digital Biomarkers For Better Personalized Treatment Of Parkinson’S Disease, 2020 (01/05/2021-30/04/2024) - Enrico Glaab

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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