In the field of statistical disclosure control, the tradeoff between dat...
Linear residualization is a common practice for confounding adjustment i...
In health related machine learning applications, the training data often...
Causal modeling has been recognized as a potential solution to many
chal...
While counterfactual thinking has been used in ML tasks that aim to pred...
Machine learning practice is often impacted by confounders. Confounding ...
Digital technologies such as smartphones are transforming the way scient...
Clinical machine learning applications are often plagued with confounder...
Clinical machine learning applications are often plagued with confounder...
The roles played by learning and memorization represent an important top...
Recently, Saeb et al (2017) showed that, in diagnostic machine learning
...