AFRICA – GE Healthcare, a subsidiary of General Electric, an American conglomerate, and is focused on the healthcare and pharmaceutical industry, has announced a suite of AI algorithms intended to lessen the clinical strain caused by COVID-19.

The eight algorithms, from Lunit INSIGHT CXR, are capable of analysing chest x-rays to find abnormalities such as tuberculosis, lung nodules and pneumonia, an indicator of COVID-19 and a key cause of mortality in those who have contracted coronavirus.

Known together as the Thoracic Care Suite, the algorithms offered by the solution flag abnormalities for review, including pneumonia, which may indicate the presence of COVID-19.

Flagged reports are sent to the PACS system where radiologists can quickly find the abnormality score for each of the eight possible abnormalities, an image overlay, and a written location description to expedite diagnosis and treatment.

“The launch of our Thoracic Care Suite is a part of GE Healthcare’s larger effort to help ensure clinicians and partners on the front lines have the equipment they need to quickly diagnose and effectively treat COVID-19 patients,” Kieran Murphy, President and CEO, GE Healthcare said in a press release.

“The pandemic has proven that data, analytics, AI and connectivity will only become more central to delivering care. For GE Healthcare, that means continuing to advance intelligent health and providing innovative technologies. This new offering is the latest example of how x-ray and AI can uphold the highest standard of patient care amidst the most modern of disease threats.”

GE Healthcare highlighted the urgency of automation in the face of increasingly large numbers of infected individuals, threatening to overwhelm healthcare facilities and professionals.

Radiologists face a particular squeeze to process and understand x-rays, with GE saying that even prior to the ongoing pandemic, with approximately 1.44 billion chest x-ray exams happening per year.

“Clinicians are looking for clinically proven methods to help identify symptoms early and determine which patients are at higher risk of complications and need to be actively monitored,” saidProfessor Fergus Gleeson, Consultant Radiologist, Professor of Radiology at the University of Oxford.

“AI can help identify these distinctions and enable hospital resources to be targeted to those that will need them whilst in hospital and following discharge.”

The solution carries a 97-99% accuracy rate (Area Under the Curve) that enables it to detect findings within seconds and allows radiologists to quickly identify high-risk cases and monitor patients showing progression and regression of mild respiratory symptoms. Results in one study showed a 34% reduction in reading time per case.

The partnership between GE and Lunit is one of the first of its kind to bring commercially available AI products from a medical AI startup to an existing X-ray equipment manufacturer, according to both companies.

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