There are a few biomarkers routinely used that can predict response to commonly prescribed therapies.
I want to make a really important distinction between demonstrating a mechanism, and showing that it has a real-world correlate, and using that to predict the future.
The standard approach is to use classifiers that predict conditions from activity patterns.
With data on coal plant locations, atmospheric conditions, and census demographics, we estimate exposure to coal plant emissions using models that predict particle transportation.
Apparently Watson's analytics can improve diagnosis and treatment, and even help prevent disease and injury by using algorithms that predict who is at highest risk.
We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions.
The model uses previous work that predicts foam flow velocity and bubble coalescence.
Loftium will determine the size of the down payment it is willing to put up using an algorithm that predicts how much income a room can generate.
However, a putative NES was identified using an algorithm that predicts leucine-rich nuclear export signals [26].
For the latter, we use a model that predicts effects on protein structure stability [ 21].
