Alaedine is a new PhD student at Limics, and will present his research subject, as well as a focus on synthetic health data. This presentation explores the role of synthetic data as a promising solution to overcome regulatory barriers in healthcare machine learning. By detailing its methodology, including regulatory compliance, reduced re-identification risks, and usability […]

Abstract: Structural Causal Models (SCMs) offer a powerful framework for understanding and reasoning about causal relationships, particularly in the context of total effects. In this presentation, we will explore a range of established tools for identifying total effects using fully specified Directed Acyclic Graphs (DAGs) derived from SCMs. These tools will be illustrated through two […]