Why are we developing this database?

Large data sets with high diversity enable us to use artificial intelligence models in practice. In this context, in the “COVID Database” project developed with volunteers specializing in medicine, it is aimed to create an extensive database about COVID-19 by combining chest x-rays and computed tomography images with detailed metadata.

The project allows doctors to examine case studies of COVID-19 patients that are affected by the newly discovered and little-known SARS-CoV-2 virus, therefore better understand the state of the patients.

Database is open-access and with the contribution of healthcare professionals and researchers, it will enable high accuracy artificial intelligence models.

Possibilities with an algorithm that can analyze pneumonia

Distinguishes COVID-19 and other types of pneumonia

Our AI distinguishes COVID-19 pneumonia and other types of pneumonia by analyzing radiological image data. The result of the analysis may lead to a preliminary diagnosis. These patients may be isolated from other patients until the test kit confirms their case. It is crucial where the healthcare capacity is limited or already reached.

Undertakes routine duties of a radiologist

It accelerates the routine reporting and analysis duties of radiologists; therefore, fewer radiologists can look after more patients. It prevents strains in the healthcare capacity.

Standalone Testing

It supports healthcare centres without test kits or with limited numbers of kits while strengthening the triage system.

Low Cost

Unlike the test kits, it does not require any extra cost and gives high accuracy results instantly as only needed equipment is the x-ray devices that most hospitals are already equipped with.

An Example of an Artificial Intelligence Model: COVID-NET

The artificial intelligence model nCoV-NET, developed by Notrino Research, detects the COVID-19 syndrome. nCoV-NET can distinguish this syndrome from other types of pneumonia.