A framework to extract, interpret and structure clinical information from free-texts
Gisele Azambuja, Tatjana Zrimec, Andrew Hopkins · Medinfo 2007: Proceedings of the 12th World Congress on Health (Medical) Informatics; Building Sustainable Health Systems · 2007
The major barrier in existing hospital information systems is that most information is stored in free-text medical narratives and is unavailable for decision support and research. Our aim is to develop a general medical text processing system to extract clinical information from different types of free-text clinical records. We propose a framework to encode and represent clinical information relying on UMLS Knowledge Resources.