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Call for Data Science and Artificial Intelligence in Public Administration selects 15 projects

(avalaible only in Portuguese)

 The final results of the Call Scientific Research and Technological Development Projects in Data Science and Artificial Intelligence in Public Administration - 2018 have been released. The 15 approved projects involve partnerships between R&D units and public administration entities, on topics such as health, public transport, water management or the use of data from the European Space Agency's IPSentinel system. In all, the projects represent an investment of almost 4 million euros over three years.

The selected projects will be presented at a public session taking place this Wednesday, October 24, at the Salão Nobre of the National Statistics Institute in Lisbon. The event will be attended by the Minister for the Presidency and Administrative Modernization, Maria Manuel Leitão Marques, and the Minister for Science, Technology and Higher Education, Manuel Heitor.

This initiative is part of the Data Science and Artificial Intelligence in Public Administration Programme, the Innovation Roadmap and axis 5 (research) of INCoDe.2030, developed by the Ministry of the Presidency and Administrative Modernization and the Ministry of Science, Technology and Higher Education. The Call aims to find innovative ways of linking data, finding patterns, anticipating failures and optimizing processes in Public Administration, in an optimization that is intended to benefit society as a whole.

See the presentations of the 15 selected projects:

iLU: Advanced Learning in Urban Data with Situational Context for Optimizing Mobility in Cities - Institute of Systems and Computer Engineering, Research and Development in Lisbon (INESC ID/INESC/IST/ULisboa) | CM Lisboa

Early detection of public transport vehicle breakdowns in an operational environment - Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) | Metro do Porto, SA

Modeling and predicting traffic accidents in the district of Setúbal - University of Évora (UE) | Setúbal Territorial Command of the National Republican Guard

IPSTERS - IPSentinel Terrestrial Reconnaissance System - Institute for the Development of New Technologies (UNINOVA/FCTUNL/UNL) | Directorate-General for Territory      

Intelligent Water Data System - Instituto Politécnico de Setúbal | Câmara Municipal do Barreiro, Empresa Municipal de Agua e Saneamento de Beja, Infraquinta

Detection of addiction patterns in online gaming - Instituto Superior de Estatística e Gestão de Informação - NOVA Information Management School (NOVA IMS) (NOVA IMS/UNL) | Turismo de Portugal, IP

Modeling the flow of students in the Portuguese education system - FCiências.ID | DGEEC

Understanding the determinants of academic performance: evidence from the Portuguese secondary education system - Instituto Superior de Estatística e Gestão de Informação - NOVA Information Management School (NOVA IMS) (NOVA IMS/UNL) | DGEEC

EPISA-Inference of Entities and Properties for Semantic Archives - Inesc Tec - Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) | Directorate-General for Books, Archives and Libraries (DGLAB)

Using Artificial Intelligence to enhance Teledermatology Screening - Fraunhofer Portugal Research Association | Administration of Shared Services of the Ministry of Health

Neuroimaging Biomarkers for the Diagnosis of Neuropsychiatric Diseases, using Artificial Intelligence - FCiências.ID | HFF (Hospital Fernando da Fonseca), HSOG (Hospital da Senhora da Oliveira, Guimarães), CHLN (Centro Hospitalar Lisboa Norte) and SPMS (Serviços Partilhados do Ministério da Saúde)

Identifying and Forecasting Demand for Hospital Emergency Departments - Calouste Gulbenkian Foundation | Administração dos Serviços Partilhados do Ministério da Saúde, E.P.E. (SPMS)

Data2Help: Data Science for Optimizing Emergency Medical Services - Institute for Systems and Computer Engineering, Research and Development in Lisbon (INESC ID/INESC/IST/ULisboa) | National Institute for Medical Emergencies (INEM)

ICDS4IM - Intelligent Clinical Decision Support in Intensive Care Medicine - University of Minho (UM) | Porto Hospital Center (CHP/MS)

Predicting the risk of complications from surgical treatment and defining prognosis in cancer patients by integrating clinical and biopathological data - Instituto de Engenharia Mecânica (IDMEC) | Instituto Português de Oncologia do Porto Francisco Gentil, EPE