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
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Keywords
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
20009 San Sebastian
Spain