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Standardisation of available and prospective data collection

Authors :
Liljeström, Mia
Renvall, Hanna
Kinnunen, Antti
Mäntynen, Ville
Montonen, Juha
Hattlestad-Hall, Christoffer
Ramírez, Federico
Maestú, Fernando
Marra, Camillo
Miraglia, Francesca
Rossini, Paolo Maria
Vecchio, Fabrizio
Haraldsen, Ira
Cruz, Andreia
Publication Year :
2022
Publisher :
Zenodo, 2022.

Abstract

This deliverable describes the shared requirements, technical solutions, and methods for collecting clinical data at the AI-Mind clinical partner sites. For that purpose, we define protocols for using research devices, materials, and clinical data handling practises to be implemented at all prospective participant visits. The clinical data will be collected at five sites in four countries (Oslo University Hospital (OUS), Oslo, Norway; Helsinki University Hospital (HUH), Helsinki, Finland; Scientific Institute for Research, Hospitalization and Healthcare, San Raffaele Roma (IRCSS) and Università Cattolica del Sacro Cuore (UCSC), Rome, Italy; Complutense University of Madrid (UCM), Madrid, Spain). The scope of this deliverable spans from acquiring the EEG/MEG data, digital cognitive testing, blood samples, and textual data from questionnaires and neuropsychological testing (NPT), to managing the (pseudonymised) clinical data at the respective sites. These protocols apply to all the clinical partners; MEG protocols will be implemented only in UCM and HUH. The AI Mind project handles both prospective (to be collected) and retrospective data (acquired earlier for other clinical and scientific purposes and included in the data transfer agreements (DTA) between the clinical sites). The emphasis of this deliverable is on the handling prospective data, but it will also define the minimum common requirements for the data handling protocols of the retrospective EEG data at the respective sites. Harmonisation of retrospective data will be further discussed in Deliverable D2.3, where also the preprocessing protocols for all the clinical MEG/EEG data are defined.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....6f38f316fddd3d76774d87ecf3c12b20
Full Text :
https://doi.org/10.5281/zenodo.7019266