Improving the conduct and reporting of newer methodological approaches Causal inference, the multidisciplinary field focused ...

Causality extraction is a rapidly evolving subfield of natural language processing that focuses on the identification and analysis of cause–effect relationships within unstructured textual data. This ...

SURD, an algorithm, reveals causal links in complex systems. Applications may include forecasting climate to projecting population growth to designing efficient aircraft. Getting to the heart of ...

In a recent study, a research team led by Assistant Professor Kazuya Sawada from the Department of Information and Computer Technology, Faculty of Engineering at Tokyo University of Science (TUS), ...

With the emergence of huge amounts of heterogeneous multi-modal data, including images, videos, texts/languages, audios, and multi-sensor data, deep learning-based methods have shown promising ...

With heart disease as the leading cause of death worldwide, there is growing recognition that recovery is not only physical but also emotional and social. A new study shows that strong and supportive ...

Getting to the heart of causality is central to understanding the world around us. What causes one variable — be it a biological species, a voting region, a company stock, or a local climate — to ...