Researchers at the Huntsman Cancer Institute at the University of Utah have successfully employed Linguamatics natural language processing software to mine patients’ electronic health records for actionable data to drive cancer research.
The Linguamatics I2E software platform extracts unstructured text contained in surgical, pathology, radiology, and clinical notes related to diseases like leukemia and lymphoma. The data is then loaded into a biobanking, clinical research, and genomic annotation platform where it can be analyzed for indicators like genetic disease predictors. Applied on a mass scale, the method allows researchers to process huge quantities of data and identify patterns that could be overlooked by analyzing individual records.
“Healthcare organizations face a major challenge to identify, capture and leverage valuable knowledge buried within vast stores of complex, unstructured patient data, and to do it in a reproducible and scalable way,” sais Phil Hastings, senior vice president of sales and marketing at Linguamatics. “We are pleased to be working with Huntsman Cancer Institute in their drive to streamline and extend their healthcare analytics efforts and positively impact research processes and patient outcomes.”