ascopubs.org

Causal Inference in Oncology Comparative Effectiveness Research Using Observational Data ...

In the article that accompanies this editorial, Lu et al 5 conducted a systematic review on the use of instrumental variable (IV) methods in oncology comparative effectiveness research. The main ...
Medical Xpress

Advancing causal inference in clinical neuroscience research

In a perspective published in Psychoradiology, researchers from Shanghai Jiao Tong University confronted causal inference in clinical neuroscience research and advocate for more clarity and ...
Nature

Causal Inference Methods in Observational Studies

Causal inference in observational settings seeks to estimate the effect of exposures, treatments or interventions on outcomes in the absence of random assignment. Unlike experimental designs, ...
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 ...
EurekAlert!

New approach to multi-hop question answering enhances robustness using causal inference

Beijing, China — Researchers from Beijing Institute of Technology and other leading institutions have developed a novel approach for improving Multi-Hop Question Answering (MHQA) tasks, which require ...
lse

Causal Inference for Observational and Experimental Studies

This course is available on the MPhil/PhD in Economic Geography, MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in Regional and Urban Planning Studies, MRes in ...
lse

Causal Inference for Observational and Experimental Studies

This course is available on the MSc in Applied Social Data Science, MSc in Behavioural Science, MSc in Human Geography and Urban Studies (Research), MSc in Innovation Policy, MSc in International ...
来自MSN

Mastering causal inference with AI support

Causal inference is transforming how researchers uncover cause-and-effect relationships, and AI is making it faster, more reproducible, and more accessible. From structured reporting standards to ...
Semiconductor Engineering

Causal Inference for AMS Design (U. of Florida)

A new technical paper, “Causal AI For AMS Circuit Design: Interpretable Parameter Effects Analysis,” was published by the University of Florida. “Analog-mixed-signal (AMS) circuits are highly ...