The reduction of health inequalities has been a priority of researchers, decision-makers and practitioners for many years.

The aim of this research therefore was to streamline the understanding of typical causal structures in both randomized and nonrandomized clinical trials in oncology, presenting concise guidelines for ...

Causal AI is redefining decision intelligence, offering deeper insights and more precise enterprise decision-making than ever before. Enterprises struggle to leverage AI for critical decisions.

We describe how ordinary interpretations of causal models and causal graphs fail to capture important distinctions among ignorable allocation mechanisms for subject selection or allocation. We ...

Earlier this year, Google began offering much more detailed answers in the top Knowledge Graph box. Shortly after that was introduced, Google also began expanding those answers into a bulleted list ...

Recent clinical trials in oncology have used increasingly complex methodologies, such as causal inference methods for intercurrent events, external control, and covariate adjustment, posing challenges ...