Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment
outcomes including efficacy and toxicity, thereby supporting the assessment and safety of …

We conducted a systematic review and meta-analysis to investigate whether the use of
statins could be associated with the risk of all-caused dementia, Alzheimer's disease (AD) …

The E-value was recently introduced on the basis of earlier work as “the minimum strength of
association… that an unmeasured confounder would need to have with both the treatment …

Background Patients with cancer have an increased risk of malnutrition which is associated
with poor outcome. The Mini Nutritional Assessment (MNA®) is often used in older patients …

Background E-values are a recently introduced approach to evaluate confounding in
observational studies. We aimed to empirically assess the current use of E-values in …

Constipation is a common community health problem. There are many factors that are
widely thought to be associated with constipation but real-world evidence of these …

Objective We aimed at providing a systematic overview of randomised trials assessing non-
pharmaceutical interventions (NPIs) to prevent COVID-19. Design Scoping review. Methods …

Background Among different investigators studying the same exposures and outcomes,
there may be a lack of consensus about potential confounders that should be considered as …

Some periodontal diseases can be associated with cariogenic bacterial growth due to
various oral health imbalances. This fact may be linked to a greater development of root …

Observational studies using causal inference frameworks can provide a feasible alternative
to randomized controlled trials. Advances in statistics, machine learning, and access to big …