Federated AI Estimates Treatment Effects Without Sharing Patient Data
Researchers have introduced VFCI, a federated framework that trains causal inference models across institutions holding different features of the same ...
Researchers have introduced VFCI, a federated framework that trains causal inference models across institutions holding different features of the same ...
A SEER analysis of 3,810 cervical cancer patients using marginal structural models and TMLE links low neighborhood income to higher ...
A new EEG and hierarchical Bayesian modeling study shows that task conditions dominate perceptual decisions in the sound-induced flash illusion, ...
Researchers built three applicability matrices covering 55 quantitative bias analysis methods to help observational researchers select appropriate bias analysis techniques ...
A two-sample Mendelian randomization study of 41 inflammatory cytokines and C-reactive protein found no significant causal effects on selected hematologic ...
A large-scale study of Türkiye's biggest gym chain identifies critical attendance periods and shows that personalized guidance and social dynamics ...
A new review surveys causal-inference methods applied to Alzheimer's molecular data, finding that many observational associations lack genetic support and ...
A new theoretical model separates two distinct forms of multisensory learning, explaining why musicians and wine tasters appear to show ...
A study of 203 oral squamous cell carcinoma patients found that the composition and functional potential of the oral microbiome ...
Researchers have formally defined the five conditions under which comparing observed outcomes with model-predicted counterfactuals yields valid treatment effect estimates.
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© 2025 Scienmag - Science Magazine