Doctors in China have been given a new powerful tool to help them quickly diagnose potential coronavirus sufferers. Called inferVISION, this AI-based software can quickly highlight potential problem cases in record time. A team of physicians in Wuhan, China, at the Zhongnan Hospital are using GPU-accelerated software to detect the visual signs of COVID-19. This AI-based software relies on NVIDIA GPUs for both training and inference and is alleviated the pressure on overworked staff to screen patients for the virus. The software is greatly helping medical staff to prioritize those who are likely to have contracted the virus. The software has been developed by a Beijing-based startup called inferVISION.

This week a Montreal-based artificial intelligence startup named Stratuscent issued a press release promising "the world's first AI-powered air quality monitor" for both Covid-19 and influenza. The company named it NOZE, since its website says it uses a "digital sense of smell" to scan the very air that you're breathing, all powered by "a single sensor built on years of NASA innovation." The website says the built-in AI component analyzes temperature, humidity, carbon dioxide, and particulate matter (as well as Covid and influenza markers). "As a connected device, it is future-proof, being able to detect new smells… as updates are pushed to it from the cloud." Units will start shipping in October (from getNOZE.com.)

Doctors in China have been given a new powerful tool to help them quickly diagnose potential coronavirus sufferers. Called inferVISION, this AI-based software can quickly highlight potential problem cases in record time. A team of physicians in Wuhan, China, at the Zhongnan Hospital are using GPU-accelerated software to detect the visual signs of COVID-19. This AI-based software relies on NVIDIA GPUs for both training and inference and is alleviated the pressure on overworked staff to screen patients for the virus. The software is greatly helping medical staff to prioritize those who are likely to have contracted the virus. The software has been developed by a Beijing-based startup called inferVISION.

As COVID-19 reaches more than 60 countries with global cases topping 95,500 and the number of death tolls crossing 3,000, the whole world is doing their best to avoid the catastrophe. While organisations like WHO and UN are releasing funds to facilitate research, many are looking towards AI to decelerate the crisis. The scientific communities across the world have galvanised to find a 21st-century solution to a 21st-century problem. Let's take a look at how AI is being used to contain the latest outbreak: DeepMind today have announced that they are releasing structure predictions of several proteins that can promote research into the ongoing research around COVID-19. They have used the latest version of AlphaFold system to find these structures.

Zhongnan Hospital of Wuhan University in Wuhan, China, is at the heart of the outbreak of Covid-19, the disease caused by the new coronavirus SARS-CoV-2 that has shut down cities in China, as well as Iran, Italy, and South Korea. That's forced the hospital to become a test bed 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 images from lung CT scans. 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. He emailed WIRED an audio file of himself answering a reporter's questions about the project and answered other questions by email.

Zhongnan Hospital of Wuhan University in Wuhan, China, is at the heart of the outbreak of Covid-19, the disease caused by the new coronavirus SARS-CoV-2 that has shut down cities in China, South Korea, Iran, and Italy. 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. He emailed WIRED an audio file of himself answering a reporter's questions about the project and answered other questions by email.

Since January 2020, the Coronavirus (2019-nCoV) outbreak at Wuhan, China, has attracted a great deal of attention from all parties in China. Everyone from Wuhan city, along with the rest of the country and world, have joined the battle to fight the Coronavirus. Currently, there are 17,205 cases of confirmed diagnosis of Coronavirus in China and 21,558 suspected cases waiting for final diagnosis. Wuhan is the epicenter, which has put an enormous amount of pressure on the local healthcare system. Working alongside, Infervision's scientists and engineering teams have successfully launched the Coronavirus AI solution; specially tailored for front-line use to help clinicians detect and monitor the disease efficiently and effectively.

Artificial intelligence is widely heralded as something that could disrupt the jobs market across the board -- potentially eating into careers as varied as accountants, advertising agents, reporters and more -- but there are some industries in dire need of assistance where AI could make a wholly positive impact, a core one being healthcare. Despite being the world's second-largest economy, China is still coping with a serious shortage of medical resources. In 2015, the country had 1.8 physicians per 1,000 citizens, according to data compiled by the Organization for Economic Cooperation and Development. That figure puts China behind the U.S. at 2.6 and was well below the OECD average of 3.4. The undersupply means a nation of overworked doctors who constantly struggle to finish screening patient scans.

At Wake Radiology in North Carolina, roughly 50 doctors scrutinize x-rays and other images for local medical providers. Within a few weeks, they should start to get help on some lung CT scans from machine-learning algorithms that highlight potentially cancerous tissue nodules. Although Wake is based in a region known as the Research Triangle, for its intensity of high-tech R&D, the lung-reading software hails from elsewhere--China. Infervision, a four-year-old Beijing startup, has amassed more than a million scans from Chinese hospitals that it's using to train and test algorithms. Gathering medical data is much easier for Chinese companies than for their US counterparts, because patient populations are larger and the burden of privacy regulations smaller. "In the US, particularly for big academic hospitals, you have to go through so many processes and it can take a really long time to access data," says Yufeng Deng, Infervision's chief scientist.

At Wake Radiology in North Carolina, roughly 50 doctors scrutinize x-rays and other images for local medical providers. Within a few weeks, they should start to get help on some lung CT scans from machine-learning algorithms that highlight potentially cancerous tissue nodules. Although Wake is based in a region known as the Research Triangle, for its intensity of high-tech R&D, the lung-reading software hails from elsewhere--China. Infervision, a four-year-old Beijing startup, has amassed more than a million scans from Chinese hospitals that it's using to train and test algorithms. Gathering medical data is much easier for Chinese companies than for their US counterparts, because patient populations are larger and the burden of privacy regulations smaller. "In the US, particularly for big academic hospitals, you have to go through so many processes and it can take a really long time to access data," says Yufeng Deng, Infervision's chief scientist.