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Artificial Intelligence in Health Care: COVID-Net Aids Triage


As the number of COVID-19 infections are again spiking around the U.S., health care workers struggling to stay ahead have a tool with a novel approach to add to their arsenal in COVID-Net, an open source AI-based platform that uses radiological lung images to determine COVID-19-specific lung damage, as well as assess the degree of that damage. The technology was developed in March, during the early days of the pandemic, but has been gaining more notice as an example of artificial intelligence in health care as more organizations have adopted it. Although the nonprofit project is being led by Red Hat, Boston Children's Hospital and DarwinAI (a 3-year-old proprietary artificial intelligence startup headquartered in Waterloo, Ontario), it began as a collaboration between Canada's University of Waterloo and DarwinAI. "COVID-Net was an initiative to try to contribute to the whirlwind of the pandemic in March," DarwinAI CEO Sheldon Fernandez told ITPro Today. "We open sourced it and we didn't want it to be commercial.

Canadian city using AI to predict who might become homeless


TORONTO – As makeshift tent cities spring up across Canada to house rough sleepers who fear using shelters due to COVID-19, one city is leveraging artificial intelligence (AI) to predict which residents risk becoming homeless. Computer programmers working for the city of London, Ontario, 170km southwest of the provincial capital Toronto, say the new system is the first of its kind anywhere – and it could offer insights for other regions grappling with homelessness. "Shelters are just packed to the brim across the country right now," said Jonathan Rivard, London's Homeless Prevention Manager, who works on the AI system. "We need to do a better job of providing resources to individuals before they hit rock bottom, not once they do," he told the Thomson Reuters Foundation. Canada is seeing a second wave of coronavirus cases, with Ontario's government warning the province could experience "worst-case scenarios seen in northern Italy and New York City" if trends continue.

Researchers find evidence of racial, gender, and socioeconomic bias in chest X-ray classifiers


Google and startups like, Aidoc, and DarwinAI are developing AI and machine learning systems that classify chest X-rays to help identify conditions like fractures, collapsed lungs, and fractures. Several hospitals including Mount Sinai have piloted computer vision algorithms that analyze scans from patients with the novel coronavirus. But research from the University of Toronto, the Vector Institute, and MIT reveals that chest X-ray datasets used to train diagnostic models exhibit imbalance, biasing them against certain gender, socioeconomic, and racial groups. Partly due to a reticence to release code, datasets, and techniques, much of the data used today to train AI algorithms for diagnosing diseases may perpetuate inequalities. A team of U.K. scientists found that almost all eye disease datasets come from patients in North America, Europe, and China, meaning eye disease-diagnosing algorithms are less certain to work well for racial groups from underrepresented countries.

How AI is helping combat homelessness in Canada during COVID-19


"It is paramount to think about not just what our data is used for, but (also) 'what can our data be used for in the future?' - and assume whoever holds the data has no scruples," said Paulo Garcia, assistant professor of computer engineering at Ottawa's Carleton University.

Reimagining the new social contract for the digital age


This TechRepublic Premium ebook compiles the latest on cancelled conferences, cybersecurity attacks, remote work tips, and the impact this pandemic is having on the tech industry. Don Tapscott is one of the world's leading authorities on the impact of technology on business and society having authored 16 widely read books. He has coined many concepts that are part of the business lexicon today and is sought by corporate and government leaders globally. Tapscott is currently co-founder and executive chairman of the Blockchain Research Institute, an adjunct professor at INSEAD, recently a two-term chancellor of Trent University in Ontario, and a Member of The Order of Canada. Tapscott is ranked the second-most influential Management Thinker and the top Digital Thinker in the world by Thinkers50.

Toronto will test Olli driverless shuttles to boost its transit system


Self-driving shuttles in North America aren't limited to the US. The city of Toronto has struck a deal with Local Motors to use the latest version of its Olli driverless shuttles as part of an automated transportation trial in spring 2021. The six- to 12-month test run will gauge how well the autonomous vehicles will bolster Toronto's mass transit system by connecting the West Rouge neighborhood with its local Go train station. The Olli 2.0 shuttles have space for up to eight passengers. Commuters won't be completely alone, though -- two staffers (one from Pacific Western Transportation and one from either TTC or Metrolinx) will be onboard to study each trip.

Recipe for selling software in a pandemic: Be essential, add some machine learning, and focus, focus, focus


Sales of software programs are already being affected by the pandemic, as seen this week in the disappointing results of Slack Technologies, makers of the popular program for team collaboration. It turns out, when companies are cutting staff, they have less need for such programs. But it turns out there is a way for a nimble software maker to thrive in the current era, namely, by bringing valuable tools to very specific parts of the market. Such is the case for thirty-year-old software vendor Prophix, based just outside of Toronto, Ontario, in Mississauga. The company sells software for the finance department of mid-sized companies for evaluating financial data and performing forecasting.

This artist used machine learning to create realistic portraits of Roman emperors


Some people have spent their quarantine downtime baking sourdough bread. But others -- namely Toronto-based artist Daniel Voshart -- have created painstaking portraits of all 54 Roman emperors of the Principate period, which spanned from 27 BC to 285 AD. The portraits help people visualize what the Roman emperors would have looked like when they were alive. Included are Voshart's best artistic guesses of the faces of emperors Augustus, Nero, Caligula, Marcus Aurelius and Claudius, among others. They don't look particularly heroic or epic -- rather, they look like regular people, with craggy foreheads, receding hairlines and bags under their eyes. To make the portraits, Voshart used a design software called Artbreeder, which relies on a kind of artificial intelligence called generative adversarial networks (GANs).

How machine learning is identifying and tracking pandemics like COVID-19


In 2003, the SARS outbreak took the world by surprise. "For me, the SARS outbreak was an eye-opening event," says Dr. Kamran Khan, infectious disease physician, professor of medicine and public health at the University of Toronto, and founder and CEO of BlueDot. "I recognized that we'd never seen anything like it before, but there would be more outbreaks like this again in the future." Khan spent the next 10 years studying infectious disease spread, looking for a way to better detect and respond to threats like SARS and the ones that followed. By 2013, machine learning technology had advanced to the point where he was able to put his vision of a digital global warning system into action -- and BlueDot was born.

Artist uses AI tech to reveal how Roman emperors would have looked


An artist has transformed the chipped stone busts of ancient Roman emperors into photorealistic portraits with the help of historical artefacts and creative software. Daniel Voshart, from Toronto, Canada, says that his project of painstakingly colourising and shaping the faces of 54 Principate rulers was'a quarantine project that got a bit out of hand', but it has attracted attention from hobbyists to historians. And he has now released his completed work in a series of stunning portraits and posters that cover 300 years of Roman history. Though more interested in design work for VR for use in architecture and the film industry, the coronavirus pandemic brought Daniel's work to stop and left him with time to explore his hobby of colourising statues. When he came to pick a subject however, he chose to research the busts of Roman Emperors who controlled its sprawling empire during the first three-century-long Principate, despite not being particularly interested in ancient history.