In a well-calibrated risk prediction model, the average predicted probab...
Monitoring the performance of machine learning (ML)-based risk predictio...
After initial release of a machine learning algorithm, the model can be
...
After deploying a clinical prediction model, subsequently collected data...
Machine learning algorithms in healthcare have the potential to continua...
The true population-level importance of a variable in a prediction task
...
Neural networks have seen limited use in prediction for high-dimensional...
Successful deployment of machine learning algorithms in healthcare requi...
Though black-box predictors are state-of-the-art for many complex tasks,...
CRISPR technology has enabled large-scale cell lineage tracing for compl...
In the regression setting, given a set of hyper-parameters, a
model-esti...
Neural networks are usually not the tool of choice for nonparametric
hig...
Antibodies, an essential part of our immune system, develop in an intric...
In high-dimensional and/or non-parametric regression problems, regulariz...