Proper

Abstract

There are huge number of biomedical ontologies and their use become ever-increasing to build context-aware systems. However, there are also exponential growths of text-based biomedical data that have prompted active research in text mining to facilitate research and create important databases. Both approaches are very useful for data annotation and analysis. Linking text mining tools with ontology in a uniform framework will enable us to achieve far more than the two approaches used separately. This article attempts to use both of these approaches for tokenizing biomedical documents in what we call context-aware tokenization. The other challenge this paper is trying to bring together developers and clinicians to use a simplified framework for prototyping and evaluation of clinical analytic systems via the use of the RapidMinor.