Collaborating Authors


Three Ways Artificial Intelligence Is Changing Medicine


We may not be at the point where you overhear your surgeon saying, "Hey, Google, pass the scalpel," but artificial intelligence (AI) is gradually making its way into the healthcare industry and, by extension, dermatology and plastic surgery practices. Even in its limited use, AI is already helping providers offer their patients better care, whether it's preop, in the OR or during the recovery process. Your experience with a medical practice starts as soon as you look for information online. You might have questions for the practitioner or want to book an appointment. In the past, you would have emailed or called the practice, but you may now find yourself speaking to an AI assistant on the practice's website.

Bringing the predictive power of artificial intelligence to health care


An important aspect of treating patients with conditions like diabetes and heart disease is helping them stay healthy outside of the hospital--before they to return to the doctor's office with further complications. But reaching the most vulnerable patients at the right time often has more to do with probabilities than clinical assessments. Artificial intelligence (AI) has the potential to help clinicians tackle these types of problems, by analyzing large datasets to identify the patients that would benefit most from preventative measures. However, leveraging AI has often required health care organizations to hire their own data scientists or settle for one-size-fits-all solutions that aren't optimized for their patients. Now the startup is helping health care organizations tap into the power of AI with a flexible analytics solution that lets hospitals quickly plug their data into machine learning models and get actionable results.

How artificial intelligence can save journalism


The economic fallout from the COVID-19 pandemic has caused an unprecedented crisis in journalism that could decimate media organizations around the world. The future of journalism -- and its survival -- could lie in artificial intelligence (AI). AI refers "to intelligent machines that learn from experience and perform tasks like humans," according to Francesco Marconi, a professor of journalism at Columbia University in New York, who has just published a book on the subject: Newsmakers, Artificial Intelligence and the Future of Journalism. Marconi was head of the media lab at the Wall Street Journal and the Associated Press, one of the largest news organizations in the world. His thesis is clear and incontrovertible: the journalism world is not keeping pace with the evolution of new technologies.

Hawaii Is Finally Making It Easier for Tourists to Visit. Is That Smart?


Hawaii is ready for its midpandemic tourism boom. Starting on Aug. 1, tourists looking to visit Hawaii will be able to bypass the state's two-week quarantine requirement for arrivals by getting a negative COVID-19 test within 72 hours before landing in the state. Visitors can also have their quarantines cut short if they receive negative test results during those two weeks. The same rules will also apply to residents returning to the islands. Hawaii won't pay for the tests; travelers will have to handle that themselves before departure, though screeners will still administer temperature checks at airports.

How robots could help injured workers recover


Training robots to guide injured workers through simulated tasks could make return-to-work evaluations and treatment programs more effective and accessible, according to researchers at the University of Alberta. In a review of scientific literature on efforts to use robotics for occupational rehabilitation, the researchers reported that robots with machine learning capabilities have the potential to accurately reproduce the physical activities workers experience and provide precise measurements of patients' abilities. "This research will hopefully improve the assessment of work ability and rehabilitation treatments, and lead to safer and more sustainable return-to-work efforts after injury," said Doug Gross, a physical therapist and professor in the Faculty of Rehabilitation Medicine. He noted the technology could be used during times of physical distancing, and expand rehabilitation services to people living in rural areas who would otherwise have to travel to access them. "You could have a therapist in Edmonton programming the robot and the patient in a rural area responding with what the therapist wants them to do," explained Gross.

Personalized surveillance for hepatocellular carcinoma in cirrhosis – Using machine learning …


Via revealing complex interactions between cancer predictors, machine learning algorithms can prove beneficial to individually evaluate HCC risk.

Malaria Detection using Deep-Learning


They may seem tiny and fragile, but mosquitoes can be extremely dangerous. Malaria has been a notoriously life-threatening disease for people of all ages which is spread by mosquitoes. More so because during the initial stages, the symptoms could easily be mistaken for fever, flu, or the common cold. But, in the advanced stages, it could wreak havoc by infecting and rupturing cell structure which could be potentially life-threatening. And if left untreated, it could even result in death.

How COVID-19 sparked a revolution in healthcare machine learning and AI – IAM Network


In the past six months, COVID-19 has evolved from a speck on the world radar to a full-blown pandemic. While it has claimed the lives of many and shed a massive spotlight on some of the major issues in healthcare, it has also served as a catalyst for innovation. As with nearly every element of the healthcare system, applications of machine learning and artificial intelligence (AI) have also been transformed by the pandemic. Although the power of machine learning and AI was being put to significant use prior to the Coronavirus outbreak, there is now increased pressure to understand the underlying patterns to help us prepare for any epidemic that might hit the world in the future. How have AI interventions fared so far?

Why Machines Still Need Humans To Stop Identity Fraud


Digital tools have become one of the only means by which consumers can communicate with their banks and other financial services, even when opening brand new accounts. The pandemic has put trust in remote digital onboarding centre stage. Government benefits, health services, online education, dating companies and gaming are just some of the sectors witnessing a huge surge in demand for digital know-your-customer (KYC) services. This is expanding the use of digital authentication at an unprecedented scale. Unfortunately, at the same time, the outbreak is proving fertile ground for fraudsters looking to exploit this global rise in digital metamorphosis.

CRISPR-based surveillance for COVID-19 using genomically-comprehensive machine learning design


The emergence and outbreak of SARS-CoV-2, the causative agent of COVID-19, has rapidly become a global concern and has highlighted the need for fast, sensitive, and specific tools to surveil circulating viruses. Here we provide assay designs and experimental resources, for use with CRISPR-based nucleic acid detection, that could be valuable for ongoing surveillance. We provide assay designs for detection of 67 viral species and subspecies, including: SARS-CoV-2, phylogenetically-related viruses, and viruses with similar clinical presentation. The designs are outputs of algorithms that we are developing for rapidly designing nucleic acid detection assays that are comprehensive across genomic diversity and predicted to be highly sensitive and specific. Of our design set, we experimentally screened 4 SARS-CoV-2 designs with a CRISPR-Cas13 detection system and then extensively tested the highest-performing SARS-CoV-2 assay.