Innovative Machine-Learning Tool Enables Researchers to Identify Patients for Clinical Trials using Clinical Notes
A natural language processing tool developed at Northwestern Medicine improves trial recruitment efforts by sorting through unstructured data to find eligible participants with rare cancers.
Using modern technology like machine learning to make better use of existing data is becoming more mainstream among healthcare providers. With virtually no limit yet in sight for the technology’s potential, a team at Northwestern Medicine decided to explore how machine learning could be applied to an unstructured and untapped area of patient data: clinician notes. The question they sought to answer was as much about investigating the capabilities of machine learning as it was about overcoming challenges to advancing patient care.