Connecting Science Data Using Semantics and Information Extraction

We are developing prototypes that explicate our vision of connecting personal medical data to scientific literature as well as to emerging grey literature (e.g., community forums) to help people find and understand information relevant to complex medical journeys. We focus on robust combinations of natural language processing along with linked data and knowledge representation to build knowledge graphs that help people make sense of current conditions and enable new manners of scientific hypothesis generation. We present our work in the context of a breast cancer use case. We discuss the benefits of biomedical linked data resources and describe some potential assistive technology for navigating rich, diverse medical content.

View Publication

Associated Projects

We aim to find new effective treatments for disease using existing drugs. Our approach is to gather and integrate existing data using semantic technologies to help discover promising drug repurposing.

Many diseases are based on genetic or epigenetic changes that can be targeted indirectly via upstream regulatory pathways. Targets need to have a high likelihood of affecting all possible changes, and so need to have upstream interactions that cover multiple genotypes/epigenotypes that might drive the same phenotype.

Sensor-based health monitors are increasing in usage and are providing growing amounts of data about our health and daily activities. These monitors are increasingly included in or integrated with mobile devices.