Project description
Remote massive screening of aged brains
Ageing populations have an increased risk for neurodegenerative diseases (NDs), including Alzheimer’s disease and Parkinson’s disease. As aged brains are highly prone to NDs, effective diagnostics are necessary. Present approaches rely on costly brain scans and laborious neuropsychological testing batteries. There is an urgent need to update them for more efficient ND detection. The EU-funded MULTI-LAND project will tackle this problem through a unique innovative interdisciplinary framework using natural language markers (NLMs) supported by machine learning. Combined with the first cross-methodological (behavioural, f/MRI, EEG) and cross-centre (Latin-America and Europe) validation of NLMs in patients with NDs, this will help optimise remote massive screening of ageing populations.
Objective
By 2030, people aged 65 and over are expected to account for more than 25% of the European population. This fact foreshadows a dramatic growth of aging-related neurodegenerative disorders (NDs), including Alzheimer's and Parkinson's disease. Critically, this scenario will place a severe strain on healthcare systems as NDs incapacitate patients, burden their families, and entail major costs of diagnostics evaluation, including time-consuming neuropsychological batteries and expensive brain scans. Though currently irreplaceable, this approach is often unaffordable and non-viable for remote application -a key requisite during pandemic lockdowns. Thus, these procedures must be complemented with urgent innovations that boost diagnosis and symptom severity detection using low-cost tools applicable to large sections of the population remotely. A promising interdisciplinary framework rooted in natural language markers (NLMs) can offer key solutions to this crisis. This novel framework is based on linguistic features derived from patient's natural speech and analysed via machine learning algorithms. NLMs are characterized by high ecological validity, minimal stress, low costs and adaptability for remote and massive screening. Despite the increasing application of NLMs in the field of mental health, their use in NDs evaluation is still scarce. Building on a unique synergy of international expertise, we will perform the first cross-methodological (behavioural, f/MRI, EEG) and cross-centre (Latin-America and Europe) validation of NLMs in patients with NDs. Specifically, we aim to: (1) establish NLMs diagnostic sensitivity, (2) unveil potential links between NLMs and brain network disruptions, (3) estimate their robustness and generalisation power. The ultimate translational goal of this project is to identify the best-performing set of NLMs to develop a frontline mobile-phone app with clinical value, capable of capturing natural speech features for remote patient evaluation.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences biological sciences neurobiology
- medical and health sciences basic medicine neurology dementia alzheimer
- medical and health sciences basic medicine neurology parkinson
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
20009 San Sebastian
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.