Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...
Recent technological advances have enabled the production of vast amounts of data types that can help health researchers better understand complex diseases, such as cancer, cardiovascular diseases and ...
High-dimensional -omics data such as genomic, transcriptomic, and metabolomic data offer great promise in advancing precision medicine. In particular, such data have enabled the investigation of ...
Cambridge, MA – Let’s say an environmental scientist is studying whether exposure to air pollution is associated with lower birth weights in a particular county. They might train a machine-learning ...
Neural responses during statistical learning reveal dissociable dynamic effects of expectation, supporting the opposing process theory within trials while demonstrating contrasting effects across ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results