Computing and visualizing informative trajectories in temporaly annotated data
Tutor / director / avaluadorGavaldà Mestre, Ricard
Tipus de documentProjecte Final de Màster Oficial
Condicions d'accésAccés obert
A trajectory in the medical world, is the sequence of events that occur during the life of a patient. In the recent years, these trajectories have been stored in the Electronical Health Records and many of the health organizations have databases with the clinical history of all their patients. The trajectories can be summarized in a trajectory graph which shows the different paths the trajectory of a patient may take. The graph contains events on its nodes and the edges contain the temporal relations. Previous works focused in the exploration of trajectory graphs only allow one event at each node, thus losing information and potentially mixing different groups of patients. In this work, we have developed a new procedure to extract the trajectory graphs that allows having several events in a single node of the graph. This procedure has been tested in two real world datasets: one related to diagnostics at hospital admissions, and the other on prescriptions in intensive care units.
Big Data Talent Awards 2017 (2n. premi)