A new open-source solution for the analysis of high content screening (HCS) data in biomedical research, has been released.

A new study reports that deep learning — a form of artificial intelligence — was able to detect malignant lung nodules on low-dose chest computed tomography scans with a performance meeting or exceeding that of expert radiologists.

UCLA researchers have identified a way to significantly reduce the duration of tuberculosis treatment using an approach called "artificial intelligence-parabolic response surface."

The Lipidomics Excellence Award (LEA) was founded to strengthen life sciences through lipidomics. After reviewing the many high-quality submitted projects, the LEA jury has announced the three awardees.

Severe weather events like tornadoes can cause a huge volume of death and property damage, with little prior notice. Now, a team of researchers are the first to directly use radiance data from a new geostationary weather satellite to help improve the warning time given for tornadoes. This article discovers how their research is harnessing the power of supercomputers to help save lives and improve safety during extreme weather events.

Dr Evangelia Petsalaki is a Group Leader at the European Bioinformatics Group, where her research team study human cell signaling in health and disease conditions. Collaborating with teams specializing in MS, imaging and cell biology, their aim is to make both predictive and conditional models so they can anticipate what might happen in a biological network under different conditions.

At the British Neuroscience Association's Festival of Neuroscience 2019, we pulled aside one of the BNA's credibility board, Dr Verena Heise to ask her about credibility in neuroscience, how she became involved in promoting it, and how other players in research can help advance the credibility cause.

Kicking off "The Evolution of Proteomics" series is a pioneer of proteomics, Professor Ruedi Aebersold. Aebersold's research in quantitative proteomics has helped shape our understanding of how proteins function, interact and are localized in both normal and diseased states.

The latest advancements in computer vision technology could be set to change the way we approach diagnostics. This rapidly evolving field uses artificial intelligence to help physicians better perform their analytical duties and improve their accuracy rate in diagnosis through medical imaging.