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Chinese Hospitals Deploy AI to Help Diagnose Covid-19


Zhongnan Hospital
Wuhan University
Zhongnan’s
Infervision
Google
Sequoia Capital
the US Centers for Disease Control
Infervision’s
Tom Simonite Infervision’s
Wuhan Tongji Hospital
China’s National Commission
Seoul National University Hospital
the Royal Adelaide Hospital
Xu
Leishenshan Hospital
National Medical Product Administration
Condé Nast
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Tom Simonite Software
Xu
Sara Harrison
Zhongnan
Kuan Chen
Hyungjin Kim
Luke Oakden-Rayner
Jeffrey Ding


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The New York Times
SOURCE: https://www.wired.com/story/chinese-hospitals-deploy-ai-help-diagnose-covid-19/
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Summary

That’s forced the hospital to become a testbed for how quickly a modern medical center can adapt to a new infectious disease epidemic.One experiment is underway in Zhongnan’s radiology department, where staff are using artificial intelligence software to detect visual signs of the pneumonia associated with Covid-19 on lung CT scan images.Haibo Xu, professor and chair of radiology at Zhongnan Hospital, says the software helps overworked staff screen patients and prioritize those most likely to have Covid-19 for further examination and testing. The software is in use at hospitals in China, and being evaluated by clinics in Europe, and the US, primarily to detect potentially cancerous lung nodules.Infervision began work on its Covid-19 detector early in the outbreak after noticing a sudden shift in how existing customers were using its lung-scan-reading software. Pneumonia associated with the disease, like other forms of viral pneumonia including that caused by SARS, produces shadows that radiologists call ground glass opacity.A paper reviewing Covid-19 lung scans published last week by Hyungjin Kim, at Seoul National University Hospital in South Korea, concluded that AI software might lessen the burden on hospitals dealing with outbreaks by helping radiologists identify patients with the disease earlier.Luke Oakden-Rayner, director of medical imaging research at the Royal Adelaide Hospital in Australia, says Infervision’s project makes him “both skeptical and cautiously optimistic.”It’s plausible that algorithms could help staff reading scans to work faster, but that would only make a significant difference to patients if radiologist time was a major bottleneck in a hospital’s operations.

As said here by Wired