Understanding the effects of weather on macroeconomic data is critically important, but it is hampered by limited time series ...

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, new statistical analysis methods are being developed to make more out of ...

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...

With the widespread application of technologies such as high-throughput sequencing, large-scale clinical trials, and complex computational ...

We present an integrated approach to derive multimodal MRI markers of cognition that can be transdiagnostically linked to psychopathology. This demonstrates that the predictive ability of neural ...

MRI decoding reveals that the inferior frontal junction-visual network reinstates target-related information as a proxy for target localization before visual search.

The AERCA algorithm performs robust root cause analysis in multivariate time series data by leveraging Granger causal discovery methods. This implementation in PyTorch facilitates experimentation on ...

Summary: A new AI framework can detect neurological disorders by analyzing speech with over 90% accuracy. The model, called CTCAIT, captures subtle patterns in voice that may indicate early symptoms ...

Background ANDROMEDA-SHOCK 2 is an international, multicenter, randomized controlled trial comparing hemodynamic phenotype-based, capillary refill time-targeted resuscitation in early septic shock to ...

Texas has won the college softball national title. After finishing as the national runners-up two times in the previous three years, the Longhorns have their first title with a 10-4 win over Texas ...

Introduction: Road traffic fatalities (RTFs) in low-resource settings like Somalia are influenced by a complex interplay of socioeconomic, environmental, and political challenges. This study ...