Artificial intelligence helps identify COVID-19 in the lungs

Artificial intelligence helps identify COVID-19 in the lungs

Spanish scientists have developed a system for the rapid identification of COVID-19 in the patient's body based on X-rays. It is based on the use of artificial intelligence.

According to a statement by the authorities of the University Hospital in Granada San Cecilio, the system for rapid confirmation of coronavirus infection was developed in cooperation with scientists from the local university, as well as employees of thirteen research centers from other provinces of Spain.


Conclusions regarding the AI-based coronavirus infection detection system have already been published in the scientific journal "Journal of Biomedical and Health". They show that several minutes after taking an X-ray of the lungs, it can be determined whether the infection with the SARS-CoV-2 virus has occurred.

Francisco Herrera, who participated in the work on the new infection identification system, from the Faculty of Artificial Intelligence at the University of Granada, indicated that the high effectiveness of the innovation developed in Spain has already been confirmed on several hundred patients.

"The effectiveness of the COVID-19 identification system developed by us ranges from 75 to 80 percent." Francisco Herrera informed.

The Spanish researcher explained that thanks to a program based on artificial intelligence, x-rays of the lungs are subjected to a quick analysis, in which other X-ray images taken in patients with COVID-19 are compared.

He added that the developed infection identification system will not expose hospitals to large expenses, because health care institutions will be able to download it in the form of an application and then coordinate it with the devices they already have.

Herrera added that the project, financed by the BBVA bank foundation with the amount of PLN 150,000 euro, will be improved from January. Spanish scientists want artificial intelligence to help them conduct a quick assessment of the stage of COVID-19 and enable the prognosis of hospitalization time of the infected person.



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