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dc.contributor.authorHaraldsen, Ira Hebold
dc.contributor.authorHatlestad-Hall, Christoffer
dc.contributor.authorMarra, Camillo
dc.contributor.authorRenvall, Hanna
dc.contributor.authorMaestú, Fernando
dc.contributor.authorAcosta-Hernández, Jorge
dc.contributor.authorAlfonsin, Soraya
dc.contributor.authorAndersson, Vebjørn
dc.contributor.authorAnand, Abhilash
dc.contributor.authorAyllón, Victor
dc.contributor.authorBabic, Aleksandar
dc.contributor.authorBelhadi, Asma
dc.contributor.authorBirck, Cindy
dc.contributor.authorBruña, Ricardo
dc.contributor.authorCaraglia, Naike
dc.contributor.authorCarrarini, Claudia
dc.contributor.authorChristensen, Erik
dc.contributor.authorCicchetti, Americo
dc.contributor.authorDaugbjerg, Signe
dc.contributor.authorDi Bidino, Rossella
dc.contributor.authorDiaz-Ponce, Ana
dc.contributor.authorDrews, Ainar
dc.contributor.authorGiuffrè, Guido Maria
dc.contributor.authorGeorges, Jean
dc.contributor.authorGil-Gregorio, Pedro
dc.contributor.authorGove, Dianne
dc.contributor.authorGovers, Tim M.
dc.contributor.authorHallock, Harry
dc.contributor.authorHietanen, Marja
dc.contributor.authorHolmen, Lone
dc.contributor.authorHotta, Jaakko
dc.contributor.authorKaski, Samuel
dc.contributor.authorKhadka, Rabindra
dc.contributor.authorKinnunen, Antti S.
dc.contributor.authorKoivisto, Anne M.
dc.contributor.authorKulashekhar, Shrikanth
dc.contributor.authorLarsen, Denis
dc.contributor.authorLiljeström, Mia
dc.contributor.authorLind, Pedro
dc.contributor.authorMarcos Dolado, Alberto
dc.contributor.authorMarshall, Serena
dc.contributor.authorMerz, Susanne
dc.contributor.authorMiraglia, Francesca
dc.contributor.authorMontonen, Juha
dc.contributor.authorMäntynen, Ville
dc.contributor.authorØksengård, Anne Rita
dc.contributor.authorOlazarán, Javier
dc.contributor.authorPaajanen, Teemu
dc.contributor.authorPeña, José M.
dc.contributor.authorPeña, Luis
dc.contributor.authorPeniche, Daniel lrabien
dc.contributor.authorSanz Perez, Ana
dc.contributor.authorRadwan, Mohamed
dc.contributor.authorRamírez-Toraño, Federico
dc.contributor.authorRodríguez-Pedrero, Andrea
dc.contributor.authorSaarinen, Timo
dc.contributor.authorSalas-Carrillo, Mario
dc.contributor.authorSalmelin, Riitta
dc.contributor.authorSousa, Sonia
dc.contributor.authorSuyuthi, Abdillah
dc.contributor.authorToft, Mathias
dc.contributor.authorToharia, Pablo
dc.contributor.authorTveitstøl, Thomas
dc.contributor.authorTveter, Mats
dc.contributor.authorUpreti, Ramesh
dc.contributor.authorVermeulen, Robin J.
dc.contributor.authorVecchio, Fabrizio
dc.contributor.authorYazidi, Anis
dc.contributor.authorRossini, Paolo Maria
dc.date.accessioned2024-03-21T06:42:11Z
dc.date.available2024-03-21T06:42:11Z
dc.date.created2024-03-15T08:42:09Z
dc.date.issued2023
dc.identifier.citationFrontiers in Neurorobotics. 2023, 17 .en_US
dc.identifier.urihttps://hdl.handle.net/11250/3123495
dc.description.abstractMore than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain stability or even revert to cognitive norms, alarmingly, up to half of the cases progress to dementia within 5 years. Current diagnostic practice lacks the necessary screening tools to identify those at risk of progression. The European patient experience often involves a long journey from the initial signs of MCI to the eventual diagnosis of dementia. The trajectory is far from ideal. Here, we introduce the AI-Mind project, a pioneering initiative with an innovative approach to early risk assessment through the implementation of advanced artificial intelligence (AI) on multimodal data. The cutting-edge AI-based tools developed in the project aim not only to accelerate the diagnostic process but also to deliver highly accurate predictions regarding an individual’s risk of developing dementia when prevention and intervention may still be possible. AI-Mind is a European Research and Innovation Action (RIA H2020-SC1-BHC-06-2020, No. 964220) financed between 2021 and 2026. First, the AI-Mind Connector identifies dysfunctional brain networks based on high-density magneto- and electroencephalography (M/EEG) recordings. Second, the AI-Mind Predictor predicts dementia risk using data from the Connector, enriched with computerized cognitive tests, genetic and protein biomarkers, as well as sociodemographic and clinical variables. AIMind is integrated within a network of major European initiatives, including The Virtual Brain, The Virtual Epileptic Patient, and EBRAINS AISBL service for sensitive data, HealthDataCloud, where big patient data are generated for advancing digital and virtual twin technology development. AI-Mind’s innovation lies not only in its early prediction of dementia risk, but it also enables a virtual laboratory scenario for hypothesis-driven personalized intervention research. This article introduces the background of the AI-Mind project and its clinical study protocol, setting the stage for future scientific contribution.en_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleIntelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocolen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.3389/fnbot.2023.1289406
dc.identifier.cristin2254610
dc.source.journalFrontiers in Neuroroboticsen_US
dc.source.volume17en_US
dc.source.pagenumber15en_US
dc.relation.projectEC/H2020/No. 964220en_US


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal