Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorHaraldsen, Ira H.en_US
dc.contributor.authorHatlestad-Hall, Christofferen_US
dc.contributor.authorMarra, Camilloen_US
dc.contributor.authorRenvall, Hannaen_US
dc.contributor.authorMaestu, Fernandoen_US
dc.contributor.authorAcosta-Hernandez, Jorgeen_US
dc.contributor.authorAlfonsin, Sorayaen_US
dc.contributor.authorAndersson, Vebjornen_US
dc.contributor.authorAnand, Abhilashen_US
dc.contributor.authorAyllon, Victoren_US
dc.contributor.authorBabic, Aleksandaren_US
dc.contributor.authorBelhadi, Asmaen_US
dc.contributor.authorBirck, Cindyen_US
dc.contributor.authorBruna, Ricardoen_US
dc.contributor.authorCaraglia, Naikeen_US
dc.contributor.authorCarrarini, Claudiaen_US
dc.contributor.authorChristensen, Eriken_US
dc.contributor.authorCicchetti, Americoen_US
dc.contributor.authorDaugbjerg, Signeen_US
dc.contributor.authorDi Bidino, Rossellaen_US
dc.contributor.authorDiaz-Ponce, Anaen_US
dc.contributor.authorDrews, Ainaren_US
dc.contributor.authorGiuffre, Guido Mariaen_US
dc.contributor.authorGeorges, Jeanen_US
dc.contributor.authorGil-Gregorio, Pedroen_US
dc.contributor.authorGove, Dianneen_US
dc.contributor.authorGovers, Tim M.en_US
dc.contributor.authorHallock, Harryen_US
dc.contributor.authorHietanen, Marjaen_US
dc.contributor.authorHolmen, Loneen_US
dc.contributor.authorHotta, Jaakkoen_US
dc.contributor.authorKaski, Samuelen_US
dc.contributor.authorKhadka, Rabindraen_US
dc.contributor.authorKinnunen, Antti S.en_US
dc.contributor.authorKoivisto, Anne M.en_US
dc.contributor.authorKulashekhar, Shrikanthen_US
dc.contributor.authorLarsen, Denisen_US
dc.contributor.authorLiljeström, Miaen_US
dc.contributor.authorLind, Pedro G.en_US
dc.contributor.authorMarcos Dolado, Albertoen_US
dc.contributor.authorMarshall, Serenaen_US
dc.contributor.authorMerz, Susanneen_US
dc.contributor.authorMiraglia, Francescaen_US
dc.contributor.authorMontonen, Juhaen_US
dc.contributor.authorMäntynen, Villeen_US
dc.contributor.authorOksengard, Anne Ritaen_US
dc.contributor.authorOlazaran, Javieren_US
dc.contributor.authorPaajanen, Teemuen_US
dc.contributor.authorPena, Jose M.en_US
dc.contributor.authorPena, Luisen_US
dc.contributor.authorPeniche, Daniel lrabienen_US
dc.contributor.authorPerez, Ana S.en_US
dc.contributor.authorRadwan, Mohameden_US
dc.contributor.authorRamirez-Torano, Federicoen_US
dc.contributor.authorRodriguez-Pedrero, Andreaen_US
dc.contributor.authorSaarinen, Timoen_US
dc.contributor.authorSalas-Carrillo, Marioen_US
dc.contributor.authorSalmelin, Riittaen_US
dc.contributor.authorSousa, Soniaen_US
dc.contributor.authorSuyuthi, Abdillahen_US
dc.contributor.authorToft, Mathiasen_US
dc.contributor.authorToharia, Pabloen_US
dc.contributor.authorTveitstol, Thomasen_US
dc.contributor.authorTveter, Matsen_US
dc.contributor.authorUpreti, Rameshen_US
dc.contributor.authorVermeulen, Robin J.en_US
dc.contributor.authorVecchio, Fabrizioen_US
dc.contributor.authorYazidi, Anisen_US
dc.contributor.authorRossini, Paolo Mariaen_US
dc.contributor.departmentDepartment of Neuroscience and Biomedical Engineeringen
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorComputer Science Professorsen
dc.contributor.groupauthorComputer Science - Artificial Intelligence and Machine Learning (AIML) - Research areaen
dc.contributor.groupauthorFinnish Center for Artificial Intelligence, FCAIen
dc.contributor.groupauthorProbabilistic Machine Learningen
dc.contributor.groupauthorProfessorship Kaski Samuelen
dc.contributor.groupauthorHelsinki Institute for Information Technology (HIIT)en
dc.contributor.organizationBioMag Laboratoryen_US
dc.date.accessioned2024-03-14T07:53:01Z
dc.date.available2024-03-14T07:53:01Z
dc.date.issued2024-01-05en_US
dc.description| openaire: EC/H2020/964220/EU//AI-Mind
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. AI-Mind 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 contributions.en
dc.description.versionPeer revieweden
dc.format.extent15
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationHaraldsen, I H, Hatlestad-Hall, C, Marra, C, Renvall, H, Maestu, F, Acosta-Hernandez, J, Alfonsin, S, Andersson, V, Anand, A, Ayllon, V, Babic, A, Belhadi, A, Birck, C, Bruna, R, Caraglia, N, Carrarini, C, Christensen, E, Cicchetti, A, Daugbjerg, S, Di Bidino, R, Diaz-Ponce, A, Drews, A, Giuffre, G M, Georges, J, Gil-Gregorio, P, Gove, D, Govers, T M, Hallock, H, Hietanen, M, Holmen, L, Hotta, J, Kaski, S, Khadka, R, Kinnunen, A S, Koivisto, A M, Kulashekhar, S, Larsen, D, Liljeström, M, Lind, P G, Marcos Dolado, A, Marshall, S, Merz, S, Miraglia, F, Montonen, J, Mäntynen, V, Oksengard, A R, Olazaran, J, Paajanen, T, Pena, J M, Pena, L, Peniche, D L, Perez, A S, Radwan, M, Ramirez-Torano, F, Rodriguez-Pedrero, A, Saarinen, T, Salas-Carrillo, M, Salmelin, R, Sousa, S, Suyuthi, A, Toft, M, Toharia, P, Tveitstol, T, Tveter, M, Upreti, R, Vermeulen, R J, Vecchio, F, Yazidi, A & Rossini, P M 2024, ' Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol ', Frontiers in Neurorobotics, vol. 17, 1289406, pp. 1-15 . https://doi.org/10.3389/fnbot.2023.1289406en
dc.identifier.doi10.3389/fnbot.2023.1289406en_US
dc.identifier.issn1662-5218
dc.identifier.otherPURE UUID: d5b98238-ecc5-4776-86aa-6418ba3c443fen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/d5b98238-ecc5-4776-86aa-6418ba3c443fen_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85186556494&partnerID=8YFLogxK
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/140948124/Intelligent_digital_tools_for_screening_of_brain_connectivity_and_dementia_risk_estimation_in_people_affected_by_mild_cognitive_impairment.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/127038
dc.identifier.urnURN:NBN:fi:aalto-202403142677
dc.language.isoenen
dc.publisherFrontiers Media
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/964220/EU//AI-Minden_US
dc.relation.ispartofseriesFrontiers in Neuroroboticsen
dc.relation.ispartofseriesVolume 17, pp. 1-15en
dc.rightsopenAccessen
dc.subject.keyword113 Computer and information sciencesen_US
dc.subject.keyword3112 Neurosciencesen_US
dc.subject.keywordAI-Minden_US
dc.subject.keywordArtificial intelligenceen_US
dc.subject.keywordClinical study protocolen_US
dc.subject.keywordDementiaen_US
dc.subject.keywordMachine learningen_US
dc.subject.keywordMild cognitive impairmenten_US
dc.subject.keywordelectroencephalography (EEG)en_US
dc.subject.keywordmagnetoencephalography (MEG)en_US
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
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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