LETHE (λήθη) – A personalized prediction and intervention model for early detection and reduction of risk factors causing dementia, based on AI and distributed Machine Learning | LETHE Project | H2020 | CORDIS

Objective

As the world's population increases in age, the number of people living with dementia grows. Dementia has long been considered to be neither preventable nor treatable, but while the underlying illnesses are not curable, today we know that the disease course might be modifiable with good preventive interventions at an early time point. The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) showed a positive effect after a 2-year intervention targeting several lifestyles and vascular risk factors simultaneously. LETHE will go beyond and provide a data-driven risk factor prediction model for older individuals at risk of cognitive decline building upon big data analysis of cross-sectional observational and longitudinal intervention datasets from 4 clinical centers in Europe including the 11- years analysis of FINGER. LETHE will establish novel digital biomarkers, for early detection of risk factors, based on unobtrusive ICT-based passive and active monitoring. The aim is to establish a digital-enabled intervention for cognitive decline prevention based on the evolution of a successful protocol (FINGER) evolving into an ICT based preventive lifestyle intervention through individualized profiling, personalized recommendations, feedback and support (FINGER 2.0), well targeted on a population stratified by cost-effective biological biomarkers. The LETHE solution will be tested in a feasibility study validating the achieved improvements. A successful LETHE project could lead to a more personalized risk factor prevention for persons with beginning cognitive decline, thereby empowering people to an active and healthy lifestyle. Expansions of prevention trials on large scale by an automatized roll out of a multimodal intervention approach, reaching out to large populations, could save future costs on expensive traditional interventions and confer benefits for the wider society.

Field of science

/natural sciences/computer and information sciences/data science/data analysis
/natural sciences/computer and information sciences/data science/big data

Funding Scheme

RIA - Research and Innovation action

Coordinator

FH JOANNEUM GESELLSCHAFT MBH

Address

Alte Poststrasse 149
8020 Graz
Austria

Activity type

Higher or Secondary Education Establishments

EU contribution

€ 642 000

LETHE (λήθη) – A personalized prediction and intervention model for early detection and reduction of risk factors causing dementia, based on AI and distributed Machine Learning

Objective

Field of science

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Call for proposal

Funding Scheme

Coordinator

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