University of California, Irvine health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is free and available online for any healthcare organization to use.

"The goal is to give an earlier alert to clinicians to identify patients who may be vulnerable at the onset," said Daniel S. Chow, an assistant professor in residence in radiological sciences and first author of the study, published in PLOS ONE.

A "nanoPCR" technology was developed for the point-of-care (POC) diagnosis of coronavirus disease-19 (COVID-19). This new technology can diagnose the infection within ~20 minutes while retaining the accuracy of conventional reverse transcription polymerase chain reaction (RT-PCR) technology.

Researchers have developed an assay that can detect the presence of SARS-CoV-2 in a nasal swab using a device attached to an ordinary smartphone, they report in the journal Cell. Although more research is needed before such a test can be rolled out, the results are promising and ultimately may be applicable to screening more broadly for other viruses.

The Nuffield Orthopaedic Centre (NOC) in Oxford has been rated highly for how it uses technology to improve patient care.

Oxford University Hospitals NHS Foundation Trust, which runs the hospital, has reached 'Stage 6' on the EMR Adoption and Maturity (EMRAM) scale, the second highest rating by the international Healthcare Information and Management Systems Society (HIMSS).

The chip, developed at Imperial College London and known as TriSilix, is a 'micro laboratory' which performs a miniature version of the polymerase chain reaction (PCR) on the spot. PCR is the gold-standard test for detecting viruses and bacteria in biological samples such as bodily fluids, faeces, or environmental samples.

Finding medicines that can kill cancer cells while leaving normal tissue unscathed is a Holy Grail of oncology research. In two new papers, scientists at UC San Francisco and Princeton University present complementary strategies to crack this problem with "smart" cell therapies - living medicines that remain inert unless triggered by combinations of proteins that only ever appear together in cancer cells.

A computer vision technology developed by University of Cambridge engineers has now been developed into a free mobile phone app for regular monitoring of glucose levels in people with diabetes.

The app uses computer vision techniques to read and record the glucose levels, time and date displayed on a typical glucose test via the camera on a mobile phone.