AI tool uses chest X-ray to identify & differentiate worst cases of COVID-19

A new artificial intelligence tool has been designed to analyze thousands of chest X-rays and differentiates between the worst cases of COVID-19. The computer programme has been developed by researchers at NYU Grossman School of Medicine. A describing detail of the latest diagnostic tool was published in the journal npj Digital Medicine on May 12.

In their study, researchers claimed that the program predicted, with 80 per cent accuracy which coronavirus patients would develop life-threatening complication within four days of contracting the infection. For this purpose, it used several hundred gigabytes of data gleaned from 5,224 chest X-rays taken from 2,943 seriously ill patients infected with SARS-CoV-2, ANI reported.  Patients’ details including weight, age, gender, race along with vital symptoms such as body temperature and blood immune cell levels were taken into consideration.

The developers have cited an immediate need to deploy such tools as coronavirus infection continues to wreak havoc across the globe. "Emergency room physicians and radiologists need effective tools like our program to quickly identify those COVID-19 patients whose condition is most likely to deteriorate quickly so that health care providers can monitor them more closely and intervene earlier," study co-lead investigator Farah Shamout, PhD, an assistant professor in computer engineering at New York University's campus in Abu Dhabi said about the new tool.

Tool to detect Coronavirus-fighting Molecules

Scientists have created a unique tool that can help drug researchers quickly identify the molecules capable of disarming the coronavirus SARS-CoV-2 before it ultimately invades the human cells. In a study published this week in Nature Machine Intelligence led by The University of New Mexico's Tudor Oprea, the researchers unveiled ‘REDIAL-2020’ which is an open-source online suite of 'computational' models that can help the scientists swiftly screen the molecules for their potential COVID-19-fighting properties.

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