concept integration from the caties to i2b2 using the umls semantic network
A tremendous wealth of valuable information is available in the plain text clinical reports and there are variety types of Natural Language Processing (NLP) platforms in place to generate concept codes and mine the reports. The information obtained from the reports has more value if it can be integrated with other clinical and genomics data. The Integrating Biology and the Bedside (i2b2) is being adopted by many institutions. Its open source based scalable framework allows research on genomics and clinical data. In this study, we have shown that any existing information extraction systems can be integrated to i2b2. In order to address this issue, the UMLS semantic network is adopted to map the concept codes generated by the Cancer Text Information Extraction System (caTIES) to i2b2. With the proposed approach, more than 200,000 sample records and 18,000 unique concept codes are made accessible and searchable instantly throughout the i2b2 infrastructure.
caties i2b2 umls semantic network the integrating biology and the bedside