COVIDLearning proposes the combination of technological solutions that will allow identifying and accessing the latest scientific evidence, mapping and synthesizing it with training models in order to improve the quantity and quality of information available to health professionals on SAR-Cov-2 to COVID-19 in Portuguese.
On the other hand, intelligent interaction tools will contribute to a dynamic community of practice of health professionals and researchers, who will be able to share with safety and scientific reliability, knowledge and experience on the clinical management of COVID-19, which will promote the continuity of interaction, use and quality of the COVIDLearning platform (
Thus, the main objectives of the COVIDLearning platform are:
1) to provide access to validated scientific literature, formative and informative content, as well as guidelines on the clinical management of COVID-19;
2) incorporate intelligent interaction tools, such as machine learning algorithms and a computer-enabled content analysis system with natural language processing, to support the promotion of practice communities aimed at health professionals and researchers.

Funding Agency

P2020 – ANI

Project Reference

Project Members

Main Project Outcomes

S. Queirós, “Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model”, in E. Puyol Antón et al. (eds) Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science, vol 13131, pp. 287-295, Springer, Cham, 2022.

“Best Paper Award in the M&Ms-2 Challenge”, by M&Ms2 Challenge organizers and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society.

Main Project Outcomes

Outputs: 1 online service has been developed and is being improved and expanded for other areas of knowledge.