Date(s) - 27 Jun 2019
4:00 pm - 5:00 pm
Making true “molecule”-“mechanism”-“observation” relationship connections is a time consuming, iterative and laborious process. In addition, it is very easy to miss critical information that affects key decisions or helps make plausible scientific connections.
The current practice for deciphering such relationships frequently involves subject matter experts (SMEs) requesting resource from busy specialized data science departments to refine and redo highly similar ad hoc searches. The result of this is impairment of both the pace and quality of scientific reviews.
In this presentation, we show how semantic integration can be made to ultimately become part of an integrated learning framework for more informed scientific decision making. We will take the audience through our pilot experiment and highlight practical learnings that should inform subsequent endeavours.
Join us by registering for the webinar. Once registered, you will receive a confirmation email about joining the webinar.