Objectives
Abstract: Public hospitals in Chile have waiting lists for specialty consultations that are both numerous and with long waiting times. The reason for referral is in the form of unstructured text and therefore it is hard for authorities to know what diseases are being consulted. As a way to automate this process and potentiate the secondary use of information we have started to annotate these referrals with the following entities: clinical finding, abbreviations, body parts, medications and family member. This talk will present preliminary results of this process.
Short Bio: Dr. Jocelyn Dunstan works at the Center for Medical Informatics, Faculty of Medicine, and the Center for Mathematical Modeling, Faculty of Mathematical and Physical Sciences, both at the University of Chile. She holds a PhD in Applied Mathematics from the University of Cambridge and a BSc and MSc in Physics from the University of Chile. Dr. Dunstan is interested in clinical text mining, in particular, the creation of computational resources to automate processes in Chilean hospitals, which can benefit the most vulnerable population (more details in https://sites.google.com/view/jdunstan/home).