Abstract Bayesian Networks (BNs) have become increasingly popular over the last few
decades as a tool for reasoning under uncertainty in fields as diverse as medicine, biology …

Human regulatory T cells (Tregs) are crucial regulators of tissue repair, autoimmune
diseases, and cancer. However, it is challenging to inhibit the suppressive function of Tregs …

Causality lays the foundation for the trajectory of our world. Causal inference (CI), which
aims to infer intrinsic causal relations among variables of interest, has emerged as a crucial …

There has been an increasing interest in methods that exploit permutation reasoning to
search for directed acyclic causal models, including the “Ordering Search''of Teyssier and …

The estimation of treatment effects is a pervasive problem in medicine. Existing methods for
estimating treatment effects from longitudinal observational data assume that there are no …

Motivation Integration of data from different modalities is a necessary step for multi-scale
data analysis in many fields, including biomedical research and systems biology. Directed …

Alterations in lipid metabolism have the potential to be markers as well as drivers of
pathobiology of acute critical illness. Here, we took advantage of the temporal precision …

Introduction Low-dose CT (LDCT) is currently used in lung cancer screening of high-risk
populations for early lung cancer diagnosis. However, 96% of individuals with detected …

Causal structure learning algorithms are very important in many fields, including biomedical
sciences, because they can uncover the underlying causal network structure from …

Etiologic diagnosis of bacterial pneumonia relies on identification of causative pathogens by
cultures, which require extended incubation periods and have limited sensitivity. Next …