Ecologists are often interested in answering causal questions from observational data but
generally lack the training to appropriately infer causation. When applying statistical analysis …

Background Antenatal pathological conditions are key in the pathogenesis of
bronchopulmonary dysplasia (BPD). Pathophysiological pathways or endotypes leading to …

Summary Background At least 5–10% of subjects surviving COVID-19 develop the post-
COVID-19 condition (PCC) or" Long COVID". The clinical presentation of PCC is …

ABSTRACT Background Plant-based diets (PBDs) are increasingly recommended for
human and planetary health. However, comprehensive evidence on the health effects of …

In this paper, we conduct a comprehensive study of Trees, Forests, and Paths within the
framework of Fuzzy and Neutrosophic Graphs. Graph theory, known for its wide-ranging …

Obtaining accurate estimates of the causal effects of socioeconomic position (SEP) on
health is important for public health interventions. To do this, researchers must identify and …

Objectives: To develop and verify a digital twin model of critically ill patient using the causal
artificial intelligence approach to predict the response to specific treatment during the first 24 …

Antibiotic resistant Klebsiella pneumoniae is a leading public health threat and
gastrointestinal carriage is an established risk factor for subsequent infections during …

Identification theory for causal effects in causal models associated with hidden variable
directed acyclic graphs (DAGs) is well studied. However, the corresponding algorithms are …

Background and Objectives To understand the course of recovery from coronavirus disease
2019 (COVID-19) among patients with multiple sclerosis (MS) and to determine its …