A world-first breakthrough by Australian researchers in ventilator splitting could help hospitals under severe stress as the number of critical COVID-19 cases continues to rise. For the first time, researchers have successfully tested, in a simulated environment, the potential to ventilate two lungs of different compliances from a single ventilator.
Social media should be used to chart the economic impact and recovery of businesses in countries affected by the COVID-19 pandemic, according to new research published in Nature Communications. University of Bristol scientists describe a 'real time' method accurately trialled across three global natural disasters which could be used to reliably forecast the financial impact of the current global health crisis.
A team of researchers in Wuhan, China have developed a multidisciplinary self-managed home quarantine method that was effective in controlling the source of COVID-19 infection and was useful in alleviating the shortage of medical resources. The case study "Implications for Online Management: Two Cases with COVID-19" describes the use of an online/offline multidisciplinary quarantine observation form,
An artificial intelligence tool accurately predicted which patients newly infected with the COVID-19 virus would go on to develop severe respiratory disease, a new study found. The work was led by NYU Grossman School of Medicine and the Courant Institute of Mathematical Sciences at New York University, in partnership with Wenzhou Central Hospital and Cangnan People's Hospital, both in Wenzhou, China.
Scientists are preparing a massive computer model of the coronavirus that they expect will give insight into how it infects in the body. They've taken the first steps, testing the first parts of the model and optimizing code on the Frontera supercomputer at the University of Texas at Austin's Texas Advanced Computing Center (TACC). The knowledge gained from the full model can help researchers design new drugs and vaccines to combat the coronavirus.
Many studies claiming that artificial intelligence is as good as (or better than) human experts at interpreting medical images are of poor quality and are arguably exaggerated, posing a risk for the safety of 'millions of patients' warn researchers in The BMJ.
Their findings raise concerns about the quality of evidence underpinning many of these studies, and highlight the need to improve their design and reporting standards.
University of Massachusetts Amherst researchers have invented a portable surveillance device powered by machine learning - called FluSense - which can detect coughing and crowd size in real time, then analyze the data to directly monitor flu-like illnesses and influenza trends.