Nature

Towards causal inference-based antidepressant selection with brain and blood biomarkers

This report sought to employ multi-modal integration of pre-treatment brain (electroencephalogram, resting-state functional magnetic resonance imaging) and blood (immune and metabolic) biomarkers to ...
CU Boulder News & Events

Causal inference under selection on observables in operations management research: Matching methods and synthetic controls

The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as ...
BMJ

Causal inference in physical activity epidemiology research: an opportunity for better evidence

Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...
mccormick.northwestern.edu

COMP_SCI 374: Causal Graphical Models

We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...
Nature

Integrating untargeted metabolomics, genetically informed causal inference, and pathway enrichment to define the obesity metabolome

Obesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in ...
Diginomica

Can causal analysis change business? Applying causality in AI and beyond

The surge in enterprise AI has fueled interest in causal analysis. In this piece, I explore the threads that bind cause and effect - and how they can be applied across a range of industry scenarios.