AIM Health
AI-based mobile applications for public health response
Description

The FCT project DSAIPA/AI/0122/2020 AIMHealth – AI-based Mobile Applications for Public Health Response, is being promoted by the Information Sciences, Technologies and Architecture Research Center (ISTAR-Iscte), in collaboration with the Center for Psychological Research and Social Intervention (CIS-Iscte), both from Iscte – University Institute of Lisbon, and as well with the Institute of Telecommunications (IT), the Association for Research and Development of the Faculty of Medicine of the University of Lisbon (AIDFM) and the Cardiovascular Center of the University of Lisbon (CCUL).

This project is funded by the Foundation for Science and Technology (FCT), according to the FCT contract DSAIPA/AI/0122/2020 under the contest “AI 4 COVID-19: Data Science and Artificial Intelligence in the Public Administration to strengthen the fight against COVID-19 and future pandemics – 2020″.

Framework

Due to the COVID-19 pandemic, personal contacts were limited, and new solutions had to be developed to prevent the spread of the virus. Some of the technological solutions presented were contact tracing applications, which inform users and authorities about the potential or current risk of spreading the virus. However, among its users, this approach has raised concerns about security and privacy.

Objective

Encompassing such concerns, this project proposes the creation and availability of a smartphone application and a safe and reliable service distribution platform based on Blockchain and Artificial Intelligence technologies, to identify symptomatic and asymptomatic patients as well as the risk exposure, providing a preventive approach to Public Health strategies.

Internal Partners
Research Centre Research Group Role in Project Begin Date End Date
ISTAR-Iscte Digital Living Spaces Partner 2021-01-25 2023-01-24
External Partners
Institution Country Role in Project Begin Date End Date
Instituto de Telecomunicações (IT) Portugal Partner 2021-01-25 2023-01-24
Association For Research, Development Of Medical School (AIDFM) Portugal Partner 2021-01-25 2023-01-24
Project Team
Name Affiliation Role in Project Begin Date End Date
Miguel Sales Dias Professor Catedrático (DTDA); Integrated Researcher (ISTAR-Iscte); Global Coordinator 2021-01-25 2023-01-24
Ana de Almeida Professora Associada (com Agregação) (DCTI); Integrated Researcher (ISTAR-Iscte); Researcher 2021-01-25 2023-01-24
Carlos Serrão Professor Associado (DTDA); Integrated Researcher (ISTAR-Iscte); Researcher 2021-01-25 2023-01-24
Joao C Ferreira or Joao Ferreira Professor Auxiliar (com Agregação) (DTDA); Integrated Researcher (ISTAR-Iscte); Researcher 2021-01-25 2023-01-24
Manoel Melo -- Researcher 2021-10-12 2022-04-11
Matilde Cascallho -- Researcher 2021-07-17 2023-01-24
Maurício Breternitz -- Researcher 2021-01-25 2023-01-24
Otávio Napoli Research Assistant (ISTAR-Iscte); Researcher 2021-10-25 2023-01-24
Sérgio Moro Professor Catedrático (DCTI); Integrated Researcher (ISTAR-Iscte); Researcher 2021-01-25 2023-01-24
Project Fundings
Reference/Code Funding DOI Funding Type Funding Program Funding Amount (Global) Funding Amount (Local) Begin Date End Date
DSAIPA/AI/0122/2020 -- Contract FCT - AI4Covid-19 - Portugal 239657.50€ 130856.25 2021-01-25 2023-01-24
Publication Outputs
Year Publication Type Full Reference
2024 Scientific journal paper Napoli, O. O., Almeida, A. M. de., Borin, E. & Breternitz Jr., M. (2024). Memory-efficient DRASiW models. Neurocomputing. 610
2024 Publication in conference proceedings Polido, S., Napoli, O., Breternitz Jr, M & Almeida, A. de (2024). Challenges in federated learning trained anomaly detection applied to hospital data without a baseline. In Proceedings 22nd IEEE Mediterranean Electrotechnical Conference (MELECON). (pp. 1230-1235). Porto: IEEE.
2023 Scientific journal paper Elvas, L. B., Ferreira, J., Dias, J. & Rosário, L. B. (2023). Health data sharing towards knowledge creation. Systems. 11 (8)
2023 Scientific journal paper Susskind, Z., Arora, A., Miranda, I. D. S., Bacellar, A. T. L., Villon, L. A. Q., Katopodis, R. F....John, L. K. (2023). ULEEN: A novel architecture for ultra low-energy edge neural networks. ACM Transactions on Architecture and Code Optimization. 20 (4)
2023 Scientific journal paper Elvas, L. B., Águas, P., Ferreira, J., Oliveira, J., Dias, J. & Rosário, L. B. (2023). AI-based aortic stenosis classification in MRI scans. Electronics. 12 (23)
2023 Scientific journal paper Elvas, L. B., Nunes, M., Ferreira, J. C., Dias, M. S. & Rosário, L. B. (2023). AI-driven decision support for early detection of cardiac events: Unveiling patterns and predicting myocardial ischemia. Journal of Personalized Medicine. 13 (9)
2023 Publication in conference proceedings Napoli, O. O., Almeida, A. M. de., Dias, J. M. S., Rosário, L. B., Borin, E. & Breternitz Jr, M. (2023). Efficient knowledge aggregation methods for weightless neural networks. In Proceedings of the 31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023). (pp. 369-374). Bruges, Belgium: ESANN.
2023 Publication in conference proceedings John, L. K., França, F. M. G., Mitra, S., Susskind, Z., Lima, P. M. V., Miranda, I. D. S....Breternitz Jr., M. (2023). Dendrite-inspired computing to improve resilience of neural networks to faults in emerging memory technologies. In 2023 IEEE International Conference on Rebooting Computing (ICRC). San Diego, CA, USA : IEEE.
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With the objective to increase the research activity directed towards the achievement of the United Nations 2030 Sustainable Development Goals, the possibility of associating scientific projects with the Sustainable Development Goals is now available in Ciência_Iscte. These are the Sustainable Development Goals identified for this project. For more detailed information on the Sustainable Development Goals, click here.

AI-based mobile applications for public health response
2021-01-25
2023-01-24