{"id":5527,"date":"2023-03-29T15:56:15","date_gmt":"2023-03-29T13:56:15","guid":{"rendered":"https:\/\/jeugdengezondheid.org\/?page_id=5527"},"modified":"2024-06-25T11:46:05","modified_gmt":"2024-06-25T09:46:05","slug":"labda","status":"publish","type":"page","link":"https:\/\/jeugdengezondheid.org\/nl\/labda\/","title":{"rendered":"LABDA"},"content":{"rendered":"\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

LABDA<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Learning Network for Advanced Behavioural Data Analysis<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"LABDA\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\n\t\t\t\t\t\t
\n\t\t\t\t\n\t\t\t\t<\/i>\t\t\t\t<\/span>\n\t\t\t<\/div>\n\t\t\t\n\t\t\t\t\t\t
\n\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tOver LABDA\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/h1>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

LABDA (Learning Network for Advanced Behavioural Data Analysis) is een Marie Sk\u0142odowska Curie Innovative Training Network (ITN) gesubsidieerd door de Europese Unie (H2021 MSCA; n\u00b0 101072993). In deze internationale onderzoekssamenwerking werken vooraanstaande wetenschappers op het gebied van de data-analyse van beweegsensoren samen om een nieuwe generatie aan creatieve en innovatieve wetenschappers op te leiden.\u00a0<\/p>

Binnen LABDA ontwikkelen we nieuwe methoden voor de data-analyse van 24-uurs beweeggedrag, gemeten door beweegsensoren. Ook onderzoeken we hoe de analyse van data van beweegsensoren kan bijdragen aan betere voorspelling van gezondheidsrisico’s. Tot slot maken we deze geavanceerde methoden makkelijker te gebruiken en te interpreteren voor wetenschap, beleid en de samenleving.\u00a0 Hiertoe worden 13 PhD-studenten opgeleid via ’training-through-research’. Samen ontwikkelen zij een classificatie voor de harmonisatie van data van verschillende bronnen.<\/p>

De resultaten worden gecombineerd in een vrij te gebruiken LABDA toolbox met geavanceerde methoden voor de analyse van data van beweegsensors. Deze toolbox is vrij toegankelijk voor onderzoekers en andere gebruikers. Deze toolbox zal leiden tot passende aanbevelingen voor de sociale gezondheid en verbeterde persoonlijke feedback op het gebied van 24-uurs beweeggedrag.\u00a0\u00a0<\/u><\/p>

3 van de 13 PhD fellows zijn ondergebracht bij Amsterdam UMC. Fellow 4 ontwikkelt nieuwe methoden voor de data-analyse van 24-uurs beweeggedrag en ontwikkelt en test voorspellende modellen voor dit gedrag. Fellow 8 classificeert de gedragsprofielen van subgroepen op een intersectionele manier en vertaalt optimale gedragsprofielen naar aanbevelingen voor de sociale gezondheid. Fellow 10 onderzoekt of geavanceerde methoden die gebruikt kunnen worden bij de ene subgroep\u00a0 met meerdere overlappende eigenschappen (zoals leeftijd, gender en ethniciteit) ook gebruikt kan worden bij andere subgroepen, en vertaalt de resultaten van deze analyses in de opzet van de LABDA toolbox.<\/p>

Wil je meer weten over LABDA? Kijk dan op de LABDA website<\/a>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Volg LABDA op<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\t\t\t
    \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t
  • \n\t\t\t\t\t \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\n <\/a>\n <\/li>\n \t\t\t\t\t\t\t\t\t\t\t\t\t\t
  • \n\t\t\t\t\t \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\n <\/a>\n <\/li>\n \t\t\t\t\t\t\t\t\t\t\t\t\t\t
  • \n\t\t\t\t\t \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/i>\n <\/a>\n <\/li>\n \t\t\t\t\t\t\t<\/ul>\n\t\t<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t
    \n\t\t\t\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t

    This project has received funding from the European Union\u2019s Horizon Europe research and innovation programme under the Marie Sk\u0142odowska-Curie grant agreement No.101072993<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

    \n\t\t\t\t\t\t
    \n\t\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t
    \n\t\t\t\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Mari\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Xin\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Teatske\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Fawad\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t

    Onderzoekers<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t\t\t

    Gaia Segantin, MSc<\/p>

    Mari Sone, MSc<\/p>

    Xin Zheng, MSc<\/p>

    Dr Fawad Taj<\/p>

    Assistant Prof Teatske Altenburg<\/p>

    Prof dr Mai Chin A Paw<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

    \n\t\t\t\t\t\t
    \n\t\t\t\t\t
    \n\t\t\t
    \n\t\t\t\t\t\t
    \n\t\t\t\t
    \n\t\t\t\t\t\t\t
    \n\t\t\t
    <\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

    LABDA Learning Network for Advanced Behavioural Data Analysis Over LABDA LABDA (Learning Network for Advanced Behavioural Data Analysis) is een Marie Sk\u0142odowska Curie Innovative Training Network (ITN) gesubsidieerd door de Europese Unie (H2021 MSCA; n\u00b0 101072993). In deze internationale onderzoekssamenwerking werken vooraanstaande wetenschappers op het gebied van de data-analyse van beweegsensoren samen om een nieuwe […]<\/p>\n","protected":false},"author":1,"featured_media":1080,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-5527","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/pages\/5527","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/comments?post=5527"}],"version-history":[{"count":47,"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/pages\/5527\/revisions"}],"predecessor-version":[{"id":6179,"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/pages\/5527\/revisions\/6179"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/media\/1080"}],"wp:attachment":[{"href":"https:\/\/jeugdengezondheid.org\/nl\/wp-json\/wp\/v2\/media?parent=5527"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}