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GE Healthcare using AI for COVID-19 chest x-rays

GE Healthcare has announce d a suite of AI algorithms intended to lessen the clinical strain caused by COVID-19

|Jun 24|magazine4 min read

GE Healthcare has announce d a suite of AI algorithms intended to lessen the clinical strain caused by COVID-19.

GE Healthcare is a subsidiary of General Electri c, the American conglomerate, and is focused on the healthcare and pharmaceutical industry.

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.

In a press release, Kieran Murphy, President and CEO, GE Healthcare, said: “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. 

“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.”

(Image: GE Healthcare)

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