The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...

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 ...

In a recent study published in PLOS One, researchers developed a causal model to analyze severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load distribution as a function of patients’ ...