Training and modernisation of public administrations and services – SATDAP – Training of Public Administration (Q2913535): Difference between revisions

From EU Knowledge Graph
Jump to navigation Jump to search
(‎Created claim: summary (P836): This Operation to which HSOG is a candidate, in close collaboration with the scientific community, aims to promote the transfer of knowledge and the adoption of advanced techniques of artificial intelligence and data science, with the aim of creating prediction models that enable the timely identification of infections automatically., translated_summary)
(‎Changed label, description and/or aliases in en: translated_label)
label / enlabel / en
 
Training and modernisation of public administrations and services – SATDAP – Training of Public Administration

Revision as of 13:16, 8 July 2021

Project Q2913535 in Portugal
Language Label Description Also known as
English
Training and modernisation of public administrations and services – SATDAP – Training of Public Administration
Project Q2913535 in Portugal

    Statements

    0 references
    0 references
    234,600.0 Euro
    0 references
    85.0 percent
    0 references
    1 November 2019
    0 references
    31 October 2021
    0 references
    HOSPITAL DA SENHORA DA OLIVEIRA GUIMARÃES, E. P. E.
    0 references
    0 references
    0 references

    41°26'30.37"N, 8°17'44.05"W
    0 references
    A presente Operação a que o HSOG se candidata, em estreita colaboração com a comunidade científica, pretende promover a transferência de conhecimento e a adoção de técnicas avançadas de inteligência artificial e ciência dos dados, com o objetivo de criar modelos de previsão que possibilitem a identificação atempada de infeções de forma automática. (Portuguese)
    0 references
    This Operation to which HSOG is a candidate, in close collaboration with the scientific community, aims to promote the transfer of knowledge and the adoption of advanced techniques of artificial intelligence and data science, with the aim of creating prediction models that enable the timely identification of infections automatically. (English)
    8 July 2021
    0 references
    Guimarães
    0 references

    Identifiers

    POCI-05-5762-FSE-000209
    0 references