A newly developed open-source patient deterioration model is improving care at the University of Michigan's health system.

Now, a study published in the British Medical Journal demonstrates that it is effective at 12 other hospital centers around the United States, outperforming the accuracy of the widely used EPIC Deterioration Index by more than 21%.

With the pandemic, there has been a rise in the use of virtual appointments for patients seeking health care. A new study by Tufts researchers, however, suggests that for many older and chronically ill patients, telehealth appointments may be most effective when they augment in-person health-care visits rather than fully replace them.

NFTs, or nonfungible tokens, created using blockchain technology, first made a splash in the art world as a platform to buy and sell digital art backed by a digital contract. But could NFT digital contracts be useful in other marketplaces? A global, multidisciplinary team of scholars in ethics, law and informatics led by bioethicists at Baylor College of Medicine wrote one of the first commentaries on how this new emerging technology could be repurposed for the healthcare industry.

As new coronavirus variants emerge and quickly spread around the globe, both the public and policymakers are faced with a quandary: maintaining a semblance of normality, while also minimizing infections. While digital contact tracing apps offered promise, the adoption rate has been low, due in part to privacy concerns.

Viruses are the largest known group of biological agents. Now, an international team of scientists with the participation of the Institute for Plant Molecular and Cellular Biology (IBMCP), a joint centre of the Universitat Politècnica de València (UPV) and the Spanish National Research Council (CSIC), has taken an important step towards understanding their diversity.

In a potential game changer for COVID-19 pandemic control efforts, a new cell phone app and lab kit have transformed a smartphone into a COVID-19 / flu detection system. The detection system is among the most rapid, sensitive, affordable and scalable tests known - and can be readily adapted for other pathogens with pandemic potential including deadly variants of COVID and flu. It also provides a platform for inexpensive home-based testing.

Computer engineers and radiologists at Duke University have developed an artificial intelligence (AI) platform to analyze potentially cancerous lesions in mammography scans to determine if a patient should receive an invasive biopsy. But unlike its many predecessors, this algorithm is interpretable, meaning it shows physicians exactly how it came to its conclusions.