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Funded Projects / details

Cofinanciado por:

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Project
Uma ferramenta de saúde pública para monitorizar o impacto de eventos disruptivos nos diagnósticos de saúde a nível nacional

Code 2024.07331.IACDC - HealthDisrupt

Beneficiary Entity

LIP - Laboratório de Instrumentação e Física Experimental de Partículas


DOI: https://doi.org/10.54499/2024.07331.IACDC


Project summary

The recent COVID-19 pandemic showed us some of the short-comings of our health systems, both by putting additional stress on professionals, and by increasing the time patients have to wait for treatment. In addition, the increased age of the population and lack of enough trained human resources has created additional stress to the system. By monitoring the effects of unexpected and expected events, policy makers can design more efficient solutions. In this project, we propose to monitor medical diagnoses in the Portuguese population, using the COVID-19 pandemic as a testcase.


Support under

Reforçar a investigação, o desenvolvimento tecnológico e a inovação

Region of Intervention

...

 

Funding

Total eligible cost

€ 124,963.00


EU financial support

€ 0.00


Funding LIP

€ 0.00


National public financial support

€ 124,963.00

 

Dates

Approval


Start

2024-11-01


End

2026-01-31

 

Acknowledgements

RE-C05-i08-m04 - "Apoiar o lançamento de um programa de projetos de I&D orientado para o desenvolvimento e implementação de sistemas avançados de cibersegurança, inteligência artificial e ciência de dados na administração pública, bem como de um programa de capacitação científica", apoiada pelo Plano de Recuperação e Resiliência (PRR),



Publications


Epidemiological methods in transition: Minimizing biases in classical and digital approachesArticle in international journal (with direct contribution from team)published

Presentations


A ilusão da inteligência: Como os dados tendenciosos podem gerar desinformação e perpetuar mitosOral presentation in advanced training events
A method to infer diagnoses from prescription dataOral presentation in international conference
A method to infer diagnoses from prescription dataOral presentation in international conference
Inferring diagnoses from prescription data: a machine-learning approachPoster presentation in international conference
Inferring diagnostics from prescription data: a machine learning approach (poster)Student presentation in advanced training event

Theses


Using online behaviour to track global outbreaks and pandemics

Team


Mariana da Cunha e Silva
Sara Raquel Araújo Basto Machado Mesquita
Tiago José de Oliveira Miranda