Biomedical Heterogeneous Data Integration and Rank Retrieval using Data Bridges

Abstract

Digitized world demands data integration systems that combine data repositories from multiple data sources. Vast amounts of clinical and biomedical research data are considered a primary force enabling data-driven research toward advancing health research and for introducing efficiencies in healthcare delivery. Data-driven research may have many goals, including but not limited to improved diagnostics processes, novel biomedical discoveries, epidemiology, and education. However, finding and gaining access to relevant data remains an elusive goal. We identified these challenges and developed an Integrated Radiology Image Search (IRIS) framework that could be a step toward aiding data-driven research. We propose building data bridges to support retrieving ranked relevant documents from integrated repository. My research focuses on biomedical data integration and indexing systems and provide ranked document retrieval from an integrated repository. Though we currently focus on integrating biomedical data sources (for medical professionals), we believe that our proposed framework and methodologies can be used in other domains as well.