The reasoning behind decisions is explainable and easily understood by humans. This is because the AI follows a deterministic approach, based on a causal graph that learns and updates in real time.

A causal model graph represents a network of interconnected entities and relationships, enabling the system to understand how various factors influence each other to create an optimized outcome.

Alembic’s composite AI solution ingests data from various sources, processes it and feeds the results into a causal graph neural network (GNN) to generate deterministic predictions and strategic ...

Recently, Quantitative Biology published an approach entitled "Gene Regulatory Network Inference based on Causal Discovery Integrating with Graph Neural Network", that leverages graph ...

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 ...

The Dornsife School of Public Health's Urban Health Collaborative and Research Office present this training that provides an introduction to DAG. DAGs are diagrams used to represent causal questions.

Graph on US abortion rate during different presidents based on real data, but needs more information Clear TikTok posts stated on June 24, 2025 in a TikTok post: ...