By analyzing carbon dioxide in the breath, an algorithm could help determine how to treat patients.

This predictive model could guide clinicians in deciding when to give potentially life-saving drugs to patients being treated for sepsis in the emergency room.

Computer scientists at Carnegie Mellon University say neural networks and supervised machine learning techniques can efficiently characterize cells that have been studied using single cell RNA-sequencing (scRNA-seq). This finding could help researchers identify new cell subtypes and differentiate between healthy and diseased cells.

NIMS and the Toyota Technological Institute at Chicago have jointly developed a Computer-Aided Material Design (CAMaD) system that enables information from thousands of scientific and technical articles to be summarized in a single chart, rationalizing and expediting material design.

Large-scale supercomputing is essential to solving complex questions about our world. But storage platforms essential for these advanced computer systems have been stuck in a rigid framework that required users to either choose between customization of features or high availability. Now, researchers have found a way to give high-performance computing data systems the flexibility to thrive with a framework called BespoKV, perhaps helping to one day achieve the HPC goal of performing at the exascale, or 1 billion billion calculations per second.

Scientists found a way of improving the crystal structure prediction algorithms, making the discovery of new compounds many times faster.

A single bacterial cell on its own is vulnerable to attack and like many living things they can benefit from safety in numbers. But bacteria take communal living to a whole new level, forming veritable civilizations - the bacterial biofilm.

As part of the host-pathogen arms race, viruses are continually evolving to evade the host immune response, be it from previous infection or immunity acquired through vaccination. Here we take a look at the processes of antigenic drift and antigenic shift.

Healthcare interoperability remains an intractable problem; both healthcare providers and patients feel unease about limited access to medical data, which results in lower care quality and poor patient engagement. Although daunting, these challenges aren’t insurmountable. In this feature, we’ll explore what has been and what could be done to foster the creation of an interoperable infrastructure.