We investigate the problem of ordering medical events in unstructured clinical narratives by learning to rank them based on their time of occurrence. We represent each medical eve...
Preethi Raghavan, Albert M. Lai, Eric Fosler-Lussi...
Nowadays, the transmission of digitized medical information has become very convenient due to the generality of Internet. Internet has created the biggest benefit to achieve the tr...
Background: The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order...
Angus Roberts, Robert J. Gaizauskas, Mark Hepple, ...
Hand-coded scripts were used in the 1970-80s as knowledge backbones that enabled inference and other NLP tasks requiring deep semantic knowledge. We propose unsupervised induction...
In this paper we present how the automatic extraction of events from text can be used to both classify narrative texts according to plot quality and produce advice in an interacti...