Predicting depression in old age: Combining life course data with machine learning

MONTORSI, Carlotta; FUSCO, Alessio; VAN KERM, Philippe; BORDAS, Stéphane

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Predicting depression in old age: Combining life course data with machine learning

MONTORSI, Carlotta; FUSCO, Alessio; VAN KERM, Philippe et al.

2022 • Well-Being conference

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https://hdl.handle.net/10993/54824

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Keywords :

Depression; Machine Learning; Aging

Research center :

LISER - Luxembourg Institute of Socio-Economic Research

Disciplines :

Special economic topics (health, labor, transportation...)

Author, co-author :

MONTORSI, Carlotta ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE)

FUSCO, Alessio ; University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE)

VAN KERM, Philippe ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Social Sciences (DSOC)

BORDAS, Stéphane ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)

External co-authors :

Language :

English

Title :

Predicting depression in old age: Combining life course data with machine learning

Publication date :

03 June 2022

Event name :

Well-Being conference

Event organizer :

STATEC

Event date :

from 01.06.2022 to 4.06.2022

Audience :

International

FnR Project :

FNR12252781 - Data-driven Computational Modelling And Applications, 2017 (01/09/2018-28/02/2025) - Andreas Zilian

Name of the research project :

Predictive well-being in old age

Funders :

FNR - Fonds National de la Recherche

Available on ORBilu :

since 08 April 2023

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