Observational studies are critical tools in clinical research and public health response, but challenges arise in ensuring ...

Causal AI, if based on flawed models or data ... significant challenges still accompany this paradigm. Further research into causalAI is not only desirable but essential, as shifting from mere ...

Researchers found that COVID-19 may accelerate biological processes linked to Alzheimer’s, showing changes in brain-related ...

An interview with Glenn Saxe, computational psychiatrist, on the limitations of our current diagnostic system, and how causal ...

Academics and other independent researchers have the most important role in improving the validity and translational capacity of research, defining clear and realistic causal questions, ensuring ...

Short-form data and analysis from Pew Research Center writers and social scientists. To view all our reports and publications, visit our main Publications page. Utah experienced the fastest growth in ...

In this paper, we establish an SAR ATR model based on causal theory. It compares the causal effect of SAR ATR between cases with ample and limited data, showing that the negative impact of the ...

If you are looking to join one of our research degree programs (PhD/Doctoral or Master’s by Research), there are three things you can do to prepare. All graduate research degrees have minimum academic ...

Causal-learn (documentation, paper) is a python package for causal discovery that implements both classical and state-of-the-art causal discovery algorithms, which is a Python translation and ...