AI and machine learning at the base of the COVIRNA diagnostic kit

10 December 2021

Although lungs are the main organs involved in COVID-19, one of the major systems affected by the virus is the cardiovascular system. The presence of pre-existing cardiovascular disease increases mortality in patients with COVID-19, and cardiovascular injuries are observed in some patients with COVID-19. It is estimated that 20% of patients infected with COVID-19 do not die from pulmonary but cardiac problems. This is precisely the issue that the COVIRNA project is trying to address.

The main goal of the project is to identify COVID-19 patients at risk of developing cardiovascular problems and look into ways they can be managed properly. The project will generate a novel diagnostic tool that will help healthcare providers improve individualised surveillance, care and follow-up of COVID-19 patients in the context of the current pandemic. COVIRNA is a great example of how healthcare can be improved by adopting a personalised medicine approach, and ultimately contribute towards alleviating the socioeconomic burden of the current COVID-19 pandemic.

Our Executive Director, George Valiotis, sat down with Dr Kanita Karađuzović-Hadžiabdić, Assistant Professor at the International University of Sarajevo, one of the COVIRNA partners. They talked about how the project started, the role of AI and machine learning in developing the COVIRNA diagnostic tool, and the extensibility of the COVIRNA project to other pandemics.

The COVIRNA project brings together 15 partners from 12 European countries. The partner organisations represent complementary expertise including academia, research, industry, health managers, and healthcare professionals.

LEARN MORE ABOUT COVIRNA
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The COVIRNA project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016072. This page and the publications contained herein only reflects the author’s views. The European Union is not liable for any use that might be made of the information contained in this page and publications.

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