Article (Scientific journals)
Progression subtypes in Parkinson's disease identified by a data driven multi cohort analysis
Hähnel, T.; Raschka, T.; Sapienza, S. et al.
2024In NPJ Parkinson's Disease, in press (in press)
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Keywords :
Parkinson's disease; Progression subtypes; cohorts; machine learning; statistics; artificial intelligence
Research center :
Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group)
Disciplines :
Life sciences: Multidisciplinary, general & others
Neurology
Biotechnology
Human health sciences: Multidisciplinary, general & others
Author, co-author :
Hähnel, T.
Raschka, T.
Sapienza, S.
Klucken, J.
GLAAB, Enrico  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Biomedical Data Science
Corvol, J.-C.
Falkenburger, B.
Fröhlich, H.
External co-authors :
yes
Language :
English
Title :
Progression subtypes in Parkinson's disease identified by a data driven multi cohort analysis
Publication date :
2024
Journal title :
NPJ Parkinson's Disease
eISSN :
2373-8057
Volume :
in press
Issue :
in press
Pages :
in press
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Systems Biomedicine
Development Goals :
3. Good health and well-being
FnR Project :
R-AGR-3931 - INTER/ERAPerMed 20/14599012/DIGIPD - GLAAB Enrico
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 17 April 2024

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