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.

With novel coronavirus spreading throughout the United States, researchers are turning to social media and artificial intelligence to track the virus as it spreads. A team headquartered at Boston Children's Hospital is implementing machine learning to scour through social posts, news reports, data from official public health channels and information supplied by doctors for warning signs that the virus is taking hold in locations outside of China. "There's incredible data that's locked away in various tools like online news sites, social media, crowdsourcing, data sources, that you wouldn't think of that would be used for public health," said Dr. John Brownstein, chief innovation officer at Boston Children's Hospital. "But actually they have incredible amounts of information that you wouldn't find in any sort of traditional government system." More than 95,000 people around the world have been infected by the outbreak of novel coronavirus, and more than 3,200 have died -- most in China.

In the months since the novel coronavirus emerged in Wuhan, China, last December, almost 2,000 research papers have been published on the health effects of the new virus, possible treatments, and the dynamics of the resulting pandemic. This outpouring of research is a testament to the speed with which science can tackle big problems. But it also presents a headache for anyone wanting to stay up to date with the literature, or hoping to mine it for insight about the virus, its behavior, or possible treatments. Naturally, some believe that artificial intelligence may help. Monday, the White House announced a project in collaboration with tech companies and academics to make a huge amount of coronavirus research accessible to AI researchers and their algorithms for the first time.

Coronavirus fears are spreading, but it's opening up options for disruptive technology to show its stuff in the wake of the outbreak. A team in Boston Children's Hospital is implementing machine learning to sift through copious amounts of online news, including social posts, news reports, data from official public health channels and information supplied by doctors to track the coronavirus. "There's incredible data that's locked away in various tools like online news sites, social media, crowdsourcing, data sources, that you wouldn't think of that would be used for public health," said Dr. John Brownstein, chief innovation officer at Boston Children's Hospital. "But actually they have incredible amounts of information that you wouldn't find in any sort of traditional government system." "Whether it's social media, online news reports, blogs, chat rooms -- we're looking for clues about symptoms, reports of disease, that tell us something unique is happening," said Brownstein.

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.

Artificial intelligence (AI) can be used to identify outbreaks such as the coronavirus, which, to date, has resulted in nearly 1,800 reported deaths and more than reported 71,000 infections. In a February 13 webinar, Casey Ross, national technology correspondent for STAT, pointed to efforts by John Brownstein, PhD, chief innovation officer at Boston Children's Hospital, to use machine learning to review social media posts, reports by physicians, news outlets, and information released by official public health entities to assess the condition's outbreak beyond China's borders. Brownstein's work is proof that AI is showing its value in tracking the outbreak of the disease, says Ross. Closer to home, healthcare systems around the country use AI to inform operational tasks such as scheduling. Some healthcare organizations use AI to pinpoint patients who need additional care, says Ross. For example, it's used in sepsis detection and prediction, the assessment of readmission risk, and the identification of patients who are deteriorating.

As the deadly 2019-nCov coronavirus spreads, raising fears of a worldwide pandemic, researchers and startups are using artificial intelligence and other technologies to predict where the virus might appear next -- and even potentially sound the alarm before other new, potentially threatening viruses become public health crises. "What we're doing currently with Coronavirus is really trying to get an understanding of what's happening on the ground through as many sources as we can get our hands on," says John Brownstein, chief innovation officer at Boston Children's Hospital and a professor at Harvard Medical School. After SARS killed 774 people around the world in the mid-2000s, his team built a tool called Healthmap, which scrapes information about new outbreaks from online news reports, chatrooms and more. Healthmap then organizes that previously disparate data, generating visualizations that show how and where communicable diseases like the coronavirus are spreading. Healthmap's output supplements more traditional data-gathering techniques used by organizations like the U.S. Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO).

With the coronavirus growing more deadly in China, artificial intelligence researchers are applying machine-learning techniques to social media, web, and other data for subtle signs that the disease may be spreading elsewhere. The new virus emerged in Wuhan, China, in December, triggering a global health emergency. It remains uncertain how deadly or contagious the virus is, and how widely it might have already spread. Infections and deaths continue to rise. More than 31,000 people have now contracted the disease in China, and 630 people have died, according to figures released by authorities there Friday.

A version of this story appeared in STAT's Health Tech newsletter. Artificial intelligence is not going to stop the new coronavirus or replace the role of expert epidemiologists. But for the first time in a global outbreak, it is becoming a useful tool in efforts to monitor and respond to the crisis, according to health data specialists. In prior outbreaks, AI offered limited value, because of a shortage of data needed to provide updates quickly. But in recent days, millions of posts about coronavirus on social media and news sites are allowing algorithms to generate near-real-time information for public health officials tracking its spread.

Companies are hard at work redefining their relationships with customers in the digital economy -- and so are healthcare systems. Boston Children's Hospital is among them, investing resources into how it can improve the "patient journey." To do that, the hospital is attempting to level data silos as well as build new processes and partnerships to improve the patient experience both within and outside its four walls. "Our thesis is that patients really expect the same service that consumers expect when they interact with the digital world," said John Brownstein, chief innovation officer at Boston Children's and a professor of biomedical informatics at Harvard Medical School. In CIO lingo, Brownstein is talking about digital transformation, where data is not just a byproduct of treating patients, but a prime driver in making the patient experience more efficient and in building patient-facing applications that could deepen the hospital-patient relationship.